US20040083090A1 - Manager for integrating language technology components - Google Patents
Manager for integrating language technology components Download PDFInfo
- Publication number
- US20040083090A1 US20040083090A1 US10/685,403 US68540303A US2004083090A1 US 20040083090 A1 US20040083090 A1 US 20040083090A1 US 68540303 A US68540303 A US 68540303A US 2004083090 A1 US2004083090 A1 US 2004083090A1
- Authority
- US
- United States
- Prior art keywords
- components
- component
- speech
- level application
- lcm
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Images
Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/28—Constructional details of speech recognition systems
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/28—Constructional details of speech recognition systems
- G10L15/32—Multiple recognisers used in sequence or in parallel; Score combination systems therefor, e.g. voting systems
Definitions
- the present invention relates generally to automated speech recognition systems and, more particularly, to the creation of speech systems from basic speech and language technology components.
- Speech and language systems include a number of discrete language technology components that are in some way tied together by the overall system.
- This speech indexing system may include a number of individually designed speech and language technology components, such as a speech recognizer component, a speaker identification component, a topic detection component, and a name extraction component.
- the speech recognizer component generates a basic text transcription of the speech.
- the other components operate on the transcription to generate additional information that describes the transcription.
- the speaker identification component provides identifications of each speaker in the transcription
- the topic detection component generates key words that define topics for segments of the transcription
- the name extraction component locates and mark all of the proper nouns in the transcription.
- Systems and methods consistent with the present invention include a Language Component Manager (LCM) that provides an interface between multiple language technology components and an external high-level application. Together, the high-level application, the LCM, and the language technology components create a complete speech system.
- the LCM marshals the interactions of the language technology components and presents a single system-level interface outside of the high-level application.
- the LCM can help to significantly simplify and expedite the creation of speech systems that use the language technology components.
- One aspect of the invention is directed to a method for interacting among components of a speech system that include language technology components, a middleware component, and at least one high-level application component.
- the method includes receiving substantially all data communications in the speech system at the middleware component and forwarding the data communications from the middleware component to a destination, one of the language technology components and the high-level application component, as determined by a configuration file.
- the method further includes receiving substantially all message communications in the speech system at the middleware component and forwarding the message communications from the middleware component to at least one of the language technology components and the high-level application component, as determined by the configuration file.
- a second aspect consistent with the invention is directed to a speech system that includes a high-level application component, language technology components, a configuration file, and a language component manager (LCM).
- the configuration file describes communication paths among the high-level application component and the language technology components.
- the LCM acts as an intermediary for communications between the high-level application component and the language technology components and between the language technology components.
- the LCM connects the high-level application component and the language technology components based on the configuration file.
- the device includes ports configured to connect with first components that perform basic speech and language processing functions.
- the device also includes at least one port configured to connect with a high-level application designed to implement a speech service using the functions provided by the first components.
- the device includes a configuration file that includes routing information that describes communication paths among the high-level application and the first components. Communication between the first components and between the first components and the high-level application are routed through the device based on the routing information in the configuration file.
- FIG. 1 is a diagram illustrating an exemplary system in which concepts consistent with the invention may be implemented
- FIG. 2 is a diagram illustrating functional relationships of the components shown FIG. 1;
- FIG. 3 is a diagram that defines states of a Language Component Manager (LCM) consistent with an aspect of the invention
- FIG. 4 is a diagram illustrating communication paths through the components shown in FIG. 2;
- FIG. 5 is a diagram illustrating a message transmitted between two components in a speech system
- FIGS. 6A and 6B are diagrams illustrating an exemplary distributed application document.
- FIG. 7 is a diagram illustrating an exemplary speech application.
- a Language Component Manager marshals the interactions (both message and data) of a group of speech and language technology components (LCs) and presents a single system-level interface to an outside application.
- the LCM takes on the responsibility of starting, shutting down, and restarting the LCs as necessary and it provides the high-level application with a well-defined system state.
- the LCM defines a framework for a fast system-abort function and it provides the LCs with a centralized logging facility.
- FIG. 1 is a diagram illustrating an exemplary system 100 in which concepts consistent with the invention may be implemented.
- System 100 includes a number of computing devices 101 that each include a computer-readable medium, such as random access memory 109 , coupled to a processor 108 .
- Computing devices 101 may also include a number of additional external or internal devices, such as, without limitation, a mouse, a CD-ROM, a keyboard, and/or a display.
- Computing devices 101 may connect to a network 102 .
- Network 102 may be, for example, a wide area network (WAN), such as the Internet, or a local area network (LAN).
- WAN wide area network
- LAN local area network
- Certain ones of computing devices 101 may connect to network 102 and to each other through a router or switch 103 .
- computing devices 101 may be any type of computing platform.
- Computing device 101 is exemplary only.
- Concepts consistent with the present invention can be implemented on any computing device, whether or not connected to a network.
- Processors 108 can be any of a number of well-known computer processors, such as processors from Intel Corporation, of Santa Clara, Calif. Processors 108 execute program instructions stored in memory 109 .
- Memory 109 may contain application programs and data.
- one of memories 109 may contain a high-level speech/language application 115 .
- Application 115 may communicate with a Language Component Manager (LCM) 116 implemented in a manner consistent with the present invention.
- LCM 116 may include software that functions as middleware between high-level application 115 and basic speech and language technology components (LCs) 117 .
- LCs 117 may include, for example, a speech recognizer component, a speaker identification component, a topic detection component, a name extraction component, or other speech or language related components.
- high-level application 115 , LCM 116 , and LCs 117 may form a complete speech system.
- Different high-level applications 115 may use different configurations of LCM 116 and LCs 117 to create different speech systems.
- High-level application 115 may, for example, use the services of LCs 117 to present an audio indexer speech system to end-users.
- High-level application 115 , LCM 116 , and LCs 117 may inter-operate with one another in a distributed manner, as is illustrated in FIG. 1. In other implementations, application 115 , LCM 116 , and LCs 117 may be implemented on a single computing device.
- FIG. 2 is a diagram illustrating functional relationships of a speech system 200 that is based on high-level application 115 , LCM 116 , and LCs 117 (labeled as LC 1 through LCn).
- LCM 116 and LCs 117 appear as a single unified service.
- High-level application 115 does not directly communicate with LCs 117 .
- high-level application 115 communicates with LCM 116 , which acts as an intermediary between high-level application 115 and LCs 117 .
- LCM 116 presents a single system-level interface to application 115 .
- LCs 117 may include speech and language processing components directed to a wide variety of basic speech technologies. As previously mentioned, these speech technologies may include speech recognition, speaker identification, topic detection, and name extraction. Techniques for implementing these technologies are known in the art and will not be further described herein.
- LCM 116 provides high-level application 115 with a well-defined system state.
- the system state is a function of the system states of LCs 117 .
- FIG. 3 is a diagram that defines the state machine for the LCM system state.
- LCM 116 may present one of five states to high-level application 115 : down state 301 , starting up state 302 , aborting state 303 , up state 304 , and shutting down state 305 .
- LCM 116 On startup of LCM 116 , the system state defaults to down state 301 . In this state, LCs 117 are not running. High-level application 115 can interact with LCM 116 only through predefined administrative interfaces.
- the administrative interfaces may allow an administrator to log into LCM 116 via, for example, a web interface or a telnet interface. With the web interface, the administrator can interact with LCM 116 through a web browser. With the telnet interface, the administrator can interact with LCM 116 through a command-line based interface. In general, the administrative interfaces allow the administrator to perform functions, such as viewing error logging information, adjusting error logging verbosity, view a current configuration file, change the LCM configuration, and interact with the LCM by posting messages.
- LCM 116 may receive a startup request through the administrative interfaces. In response to the startup request, LCM 116 starts LCs 117 and enters starting up state 302 .
- LCs 117 may be started based on initialization information contained in a configuration file, called a distributed application document. When started, LCs 117 may boot-up and open a communication channel with LCM 116 . If any of LCs 117 fail to connect within a pre-specified timeout period, LCM 116 assumes a non-recoverable failure of the LC 117 and changes the system state to shutting down state 305 .
- an LC 117 When an LC 117 reaches a state of operational readiness (e.g., it has loaded and processed its model data), it reports its state to LCM 116 .
- LCM 116 may respond by activating data and message connections.
- LCM 116 enters up state 304 .
- Up state 304 is the primary operational state of LCM 116 .
- LCM 116 is responsible for managing data and message communications between LCs 117 and high-level application 115 . While in up state 304 , LCM 116 may monitor LCs 117 for failure and switch its state to shutting down state 305 in the event of a failure.
- LCM 116 may discontinue data and message routing activities between the various components (i.e., LCs and high-level applications). LCM 116 may then disconnect any connected high-level applications 115 and subsequently instruct all LCs 117 to shut down. When these actions are complete, LCM 116 may enter down state 301 .
- Administrators or high-level applications 115 may issue abort requests to LCM 116 to disconnect from LCM 116 .
- LCM 116 may respond by entering aborting state 303 . In this state, LCM 116 deactivates message and data routing between the LCs 117 and the aborting high-level application or administrator.
- LCM 116 can control instabilities due to random timing problems between LCs 117 . More particularly, because LCM 116 controls all communications between components in system 200 , LCM 116 , in the event of an error, can shut down the components in an orderly manner and, thus, avoid system race conditions.
- FIG. 4 is a diagram illustrating communication paths in system 200 .
- LC 1 communicates with LCn through LCM 116 .
- high-level application 115 and LC 1 -LCn communicate with one another through LCM 116 .
- a benefit of this communication framework is that it minimizes port management inside the LCs and the high-level applications, such as application 115 .
- LCs 117 and high-level applications 115 only need to communicate with one entity—LCM 116 .
- the LCM communication framework may provide two ways for communicating: message and data.
- Message communication can be conceptualized as an asynchronous remote procedure call by an initiating component to a receiving component.
- Message communication is generally used to initiate actions in LCs 117 .
- Data communication provides a way to pass data units between components, where these data units do not invoke actions in the receiving component. Instead, the data units are processed by the receiving component.
- FIG. 5 is a diagram illustrating a message 501 transmitted between two LCs 117 , labeled as LC 1 and LC 2 .
- Message 501 is a simple message that instructs LC 2 to take a particular action.
- Message 501 has a one-to-one relationship between components, i.e., there is one sender (LC 1 ) and one receiver (LC 2 ) of the message.
- LCM 116 may also support m:n message relationships, in which there can be m senders and n receivers of one particular message, where both m and n are greater than or equal to one.
- a message can be sent from any one of the m senders for delivery to each of the n receivers.
- Table I illustrates a number of possible system messages that relate to the control of LCM 116 .
- LCM_ABORT While executing a system-abort operation, the LCM will send an ⁇ LCM_ABORT/>to every component (LCs and high-level applications), instructing them to discontinue any system-related activities, reset themselves and then report their readiness.
- LCM_ABORT_DONE Once a component has reacted appropriately to an abort request from the LCM, it notifies the LCM of its return to operational readiness by sending an ⁇ LCM_ABORT_DONE/>.
- LCM_READY An LC sends an ⁇ LCM_READY/> message to the LCM when it has reached operational readiness.
- LCM_SHUTDOWN The LCM will send an ⁇ LCM_SHUTDOWN/> message to an LC to instruct the LC to shut itself down.
- LCM_SYSTEM_ABORT A high-level application can send an ⁇ LCM_SYSTEM_ABORT/> message to the LCM to initiate a system-abort.
- LCM_SYSTEM_READY An ⁇ LCM_SYSTEM_READY/> will be distributed to all LCs and (potentially connected) high-level applications, when the entire system has reached a state of operational readiness, i.e. when the system state is changed to up.
- the purpose of data communication between components is to pass data units, such as packets, of structured information between the components.
- data communication does not generally invoke actions in the receiving component. Instead, the receiving component consumes or processes the information contained in the packets.
- a data pipe model is used to pass data between components.
- the data pipe may be a one-to-one relationship between the component that sends/produces data and the component that receives/consumes the data.
- a data pipe may be implemented by the producer by sending the following pieces of information to LCM 116 : the name of the data pipe, a data pipe command, and any arguments required by the data pipe command. LCM 116 will then deliver the data pipe command and its arguments (if any) to the appropriate data-pipe consumer.
- a data pipe may be configured to connect multiple LCs 117 in series. In this manner, data produced by a first LC may be consumed by a second LC, which may then produce a modified version of the data which may then be consumed by a third LC.
- Table II lists three exemplary data pipe commands. TABLE II Com- Return-value mand Argu- (besides Command ID ments Effect error code) Clear data- 3 None Instruct the data None pipe consumer to remove any unprocessed data packets that it has in its data- receiving buffer Get number 4 None Instruct the data Unsigned of elements consumer to return the integer, in data-pipe number of data packets indicating the buffer that are currently held in number of data the data-receiving buffer. packets that are currently in the data-receiving buffer. Send data 1 Data Delivers a data packet to None packet the data-pipe consumer. The data-packet can be rejected by the data- consumer using the error code BufferFull. In this case, the data producer is responsible for retransmitting the data packet at a later time.
- DAD distributed application document
- the DAD is an XML document that describes in detail the configuration of an LCM-managed system.
- LCM 116 parses the DAD in determining the configuration of speech system 200 .
- a particular system configuration may define the specification of LCs 117 , the specification of high-level application 115 , the message and data communication connections between all the components, and error logging settings.
- the DAD can be viewed as a complete system specification.
- FIGS. 6A and 6B illustrate an exemplary DAD 600 .
- the DAD shown in FIG. 6 is a simplified version of a typical DAD.
- DAD 600 includes a name tag 601 that includes the name of the particular high-level application.
- the application is “Audio Indexer.”
- Run-time section 602 may include, during run-time, a list of all connected LCs 117 and high-level applications 115 . These run-time connections may be dynamically changed by LCM 116 as the connected components change. In this example, run-time section 602 also includes an auto-start tag that indicates that DAD 600 is to be automatically loaded by LCM 116 when LCM 116 is initially started.
- the system specification section located between the tags “ ⁇ SYSTEM_SPECIFICATION>” (FIG. 6A) and “ ⁇ /SYSTEM_SPECIFICATION>” (FIG. 6B), includes a complete description of the configuration of the components in speech system 200 , including the message and data paths.
- the “SYSTEM_SPECIFICATION” section includes a “CONNECTION_LISTENERS” section, a “LOGGING_TARGETS” section, a “MESSAGES” section, a “DATA_PIPES” section (FIG. 6B), a “REMOTE_APPLICATIONS” section (FIG. 6B), and a “LANGUAGE_COMPONENTS” section (FIG. 6B).
- brackets (“ ⁇ . . . >”) denote the beginning of a section and brackets with a slash (“ ⁇ / . . . >”) denote the end of a section.
- the CONNECTION_LISTENERS section includes a number of CONNECTION_LISTENER tags that define the low-level connections between the components, including the port of LCM 116 with which the components connect. Additionally, these tags may also define whether each port is a port dedicated to a data producer, data consumer, or message.
- the LOGGING_TARGETS section defines error logging settings for the system, such as target file names. Additionally, the level of detail to which errors are logged can be set in this section through the verbosity setting. Valid values for the verbosity setting according to one implementation consistent with the invention are shown in Table III. TABLE III Logging Level Description None No logging information. Error Indicates a severe exception condition in the LC. This condition often leads to component failure and hence to system shutdown. Warning Unexpected exception-like condition. The LC can avoid failure but this is still a severe exception. Info Provides high-level component state information that might be of general interest. Detail Provide very fine-grain detailed information about the component's system state. This type of information is typically useful for component debugging.
- the MESSAGES section defines the possible flow of messages between the components in speech system 200 .
- the MESSAGES section may include three subsections: “PUBLIC_IN”, “PUBLIC_OUT”, and “PRIVATE.”
- PUBLIC_IN refers to messages generated by high-level application 115 and transmitted to LCM 116 .
- PUBLIC_OUT refers to messages from LCM 116 and transmitted to high-level applications 115 .
- PRIVATE refers to messages transmitted between LCs 117 via LCM 116 .
- Each entry 604 in the PUBLIC_OUT sub-section includes a message name (“message name” field), the name of the LC from which the message originates (“from” field), and the name of the destination high-level application (“to”) field.
- the messages are all destined for the application “decode.”
- the messages named “passage” and “gap” originate from the LCs identified as “spk_segment.”
- the message named “word” originates from the LC named “nbscore.”
- the LC named “nbscore” may transmit a message to the LCM that includes the label “word.”
- LCM 116 based on DAD 600 , knows that this message should be forwarded to the high-level application “decode.”
- the DATA_PIPES section defines the possible flow of data between the components in system 200 .
- the DATA_PIPES section may include the three sub-sections PUBLIC_IN, PUBLIC_OUT, and PRIVATE. These sections similarly define data pipes between high-level applications 115 and LCM 116 , between LCM 116 and the high-level applications, and between LCs, respectively.
- Two exemplary data pipe entries are shown in DAD 600 under the PRIVATE sub-section of DATA_PIPES.
- the first data pipe entry is named “phn2seq.” This data pipe is received by LCM 116 from the LC “filter_component” and forwarded to the LC “speaker_seg.”
- the second data pipe entry is named “seg2fw.” Data transmitted through this data pipe is received by LCM 116 from the LC “speaker_seg” and forwarded to the LC “decoder_fw.”
- the “REMOTE_APPLICATIONS” section defines high-level applications 115 that connect to LCM 116 .
- One remote application, named “feed_audio” is illustrated as being defined in this section.
- the “LANGUAGE_COMPONENTS” section defines LCs 117 that may communicate with LCM 116 .
- One LC 117 named “decoder_phn” is defined in this section.
- FIG. 7 is a diagram illustrating components in an exemplary speech application.
- the speech application shown in FIG. 7 may be a dialog manager that recognizes speech received over a telephone connection and takes action based on the instructions from the telephone caller.
- High-level application 701 may include a dialog manager application that responds to speech-based commands from the caller and generates appropriate responses for the caller.
- the speech processing used to recognize the commands in the speech is primarily performed by LCs 703 - 707 .
- LCs 703 - 707 include DTMF (dual-tone multi-frequency) recognizer component 703 , voice-over-IP (VoIP) component 704 , speech segmenter component 705 , text-to-speech component 706 , and speech recognizer component 707 .
- DTMF component 703 is configured to recognize key presses on a touch-tone telephone based on the corresponding DTMF signal generated by the telephone.
- VoIP component 704 receives the user's telephone call.
- the telephone call is received as a packetized signal in a VoIP connection.
- Speech segmenter component 705 segments speech signals into useful segments. Speech segmenter component 705 may, for example, segment input speech signals into audio segments corresponding to individual words or sentences. Text-to-speech component 706 may generate synthesized speech signals based on input text documents. Speech recognizer component 707 performs basic speech recognition of input speech signals.
- LCM 702 acts as an intermediary between high-level application 701 and LCs 703 - 707 .
- LCM 702 reads a DAD document to determine the message and data interactions between high-level application 701 and LCs 703 - 707 .
- the DAD may dictate that speech received at VoIP component 704 is to be transmitted via a data pipe to speech segmenter component 705 .
- the output of speech segmenter component 705 may be forwarded to speech recognizer component 707 , the output of which may then be forwarded to high-level application 701 .
- high-level application 701 may respond to callers by generating text that it transmits, via LCM 702 , to text-to-speech component 706 .
- the synthesized text output from text-to-speech component 706 may then be transmitted to VoIP component 704 for transmission to the caller.
- the data is transmitted through and routed by LCM 702 .
- An LCM functions as middleware between one or more language and technology components and one or more high-level applications.
- the LCM, the language and technology component(s), and the high-level application(s) form a speech system.
- the components of the speech system may be distributed. All data and messages in the speech system pass through the LCM.
- a configuration file defines relationships, such as message and data paths, for the speech system.
- the software may more generally be implemented as any type of logic.
- This logic may include hardware, such as application specific integrated circuit or a field programmable gate array, software, or a combination of hardware and software.
Abstract
Description
- This application claims priority under 35 U.S.C. § 119 based on U.S. Provisional Application No. 60/419,214 filed Oct. 17, 2002, the disclosure of which is incorporated herein by reference.
- A. Field of the Invention
- The present invention relates generally to automated speech recognition systems and, more particularly, to the creation of speech systems from basic speech and language technology components.
- B. Description of Related Art
- Many speech and language systems include a number of discrete language technology components that are in some way tied together by the overall system. Consider a speech indexing system that is designed to receive an audio signal, convert speech in the audio signal to a text transcription, and annotate the text to include additional information derived from the speech. This speech indexing system may include a number of individually designed speech and language technology components, such as a speech recognizer component, a speaker identification component, a topic detection component, and a name extraction component.
- The speech recognizer component generates a basic text transcription of the speech. The other components operate on the transcription to generate additional information that describes the transcription. Thus, the speaker identification component provides identifications of each speaker in the transcription, the topic detection component generates key words that define topics for segments of the transcription, and the name extraction component locates and mark all of the proper nouns in the transcription.
- These basic language technology components may be reused in numerous other speech systems. Conventionally, when designing a new speech system, the designer manually integrates each of the basic language technology components into the system. This may involve individually controlling the start-up and handling of error conditions from the language technology components. Additionally, the designer may manually design structures for controlling the flow of data and control information between the language technology components. Significant resources may be spent on integrating the language technology components into the speech system.
- Thus, there is a need in the art to improve the integration of basic language technology components into a high-level speech system.
- Systems and methods consistent with the present invention include a Language Component Manager (LCM) that provides an interface between multiple language technology components and an external high-level application. Together, the high-level application, the LCM, and the language technology components create a complete speech system. The LCM marshals the interactions of the language technology components and presents a single system-level interface outside of the high-level application. The LCM can help to significantly simplify and expedite the creation of speech systems that use the language technology components.
- One aspect of the invention is directed to a method for interacting among components of a speech system that include language technology components, a middleware component, and at least one high-level application component. The method includes receiving substantially all data communications in the speech system at the middleware component and forwarding the data communications from the middleware component to a destination, one of the language technology components and the high-level application component, as determined by a configuration file. The method further includes receiving substantially all message communications in the speech system at the middleware component and forwarding the message communications from the middleware component to at least one of the language technology components and the high-level application component, as determined by the configuration file.
- A second aspect consistent with the invention is directed to a speech system that includes a high-level application component, language technology components, a configuration file, and a language component manager (LCM). The configuration file describes communication paths among the high-level application component and the language technology components. The LCM acts as an intermediary for communications between the high-level application component and the language technology components and between the language technology components. The LCM connects the high-level application component and the language technology components based on the configuration file.
- Yet another aspect consistent with the present invention is directed to a system integration device. The device includes ports configured to connect with first components that perform basic speech and language processing functions. The device also includes at least one port configured to connect with a high-level application designed to implement a speech service using the functions provided by the first components. Still further, the device includes a configuration file that includes routing information that describes communication paths among the high-level application and the first components. Communication between the first components and between the first components and the high-level application are routed through the device based on the routing information in the configuration file.
- The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate the invention and, together with the description, explain the invention. In the drawings,
- FIG. 1 is a diagram illustrating an exemplary system in which concepts consistent with the invention may be implemented;
- FIG. 2 is a diagram illustrating functional relationships of the components shown FIG. 1;
- FIG. 3 is a diagram that defines states of a Language Component Manager (LCM) consistent with an aspect of the invention;
- FIG. 4 is a diagram illustrating communication paths through the components shown in FIG. 2;
- FIG. 5 is a diagram illustrating a message transmitted between two components in a speech system;
- FIGS. 6A and 6B are diagrams illustrating an exemplary distributed application document; and
- FIG. 7 is a diagram illustrating an exemplary speech application.
- The following detailed description of the invention refers to the accompanying drawings. The same reference numbers may be used in different drawings to identify the same or similar elements. Also, the following detailed description does not limit the invention. Instead, the scope of the invention is defined by the appended claims and equivalents of the claim limitations.
- A Language Component Manager (LCM) marshals the interactions (both message and data) of a group of speech and language technology components (LCs) and presents a single system-level interface to an outside application. The LCM takes on the responsibility of starting, shutting down, and restarting the LCs as necessary and it provides the high-level application with a well-defined system state. In addition, the LCM defines a framework for a fast system-abort function and it provides the LCs with a centralized logging facility.
- Speech-related applications and systems, as described herein, may be performed on one or more processing devices or networks of processing devices. FIG. 1 is a diagram illustrating an
exemplary system 100 in which concepts consistent with the invention may be implemented.System 100 includes a number ofcomputing devices 101 that each include a computer-readable medium, such asrandom access memory 109, coupled to aprocessor 108.Computing devices 101 may also include a number of additional external or internal devices, such as, without limitation, a mouse, a CD-ROM, a keyboard, and/or a display. -
Computing devices 101 may connect to anetwork 102.Network 102 may be, for example, a wide area network (WAN), such as the Internet, or a local area network (LAN). Certain ones ofcomputing devices 101 may connect tonetwork 102 and to each other through a router or switch 103. - In general,
computing devices 101 may be any type of computing platform.Computing device 101 is exemplary only. Concepts consistent with the present invention can be implemented on any computing device, whether or not connected to a network. -
Processors 108 can be any of a number of well-known computer processors, such as processors from Intel Corporation, of Santa Clara, Calif.Processors 108 execute program instructions stored inmemory 109. -
Memory 109 may contain application programs and data. In particular, as shown in FIG. 1, one ofmemories 109 may contain a high-level speech/language application 115.Application 115 may communicate with a Language Component Manager (LCM) 116 implemented in a manner consistent with the present invention.LCM 116 may include software that functions as middleware between high-level application 115 and basic speech and language technology components (LCs) 117.LCs 117 may include, for example, a speech recognizer component, a speaker identification component, a topic detection component, a name extraction component, or other speech or language related components. Together, high-level application 115,LCM 116, andLCs 117 may form a complete speech system. Different high-level applications 115 may use different configurations ofLCM 116 andLCs 117 to create different speech systems. High-level application 115 may, for example, use the services ofLCs 117 to present an audio indexer speech system to end-users. - High-
level application 115,LCM 116, andLCs 117 may inter-operate with one another in a distributed manner, as is illustrated in FIG. 1. In other implementations,application 115,LCM 116, andLCs 117 may be implemented on a single computing device. - FIG. 2 is a diagram illustrating functional relationships of a
speech system 200 that is based on high-level application 115,LCM 116, and LCs 117 (labeled as LC1 through LCn). To high-level application 115,LCM 116 andLCs 117 appear as a single unified service. High-level application 115 does not directly communicate withLCs 117. Instead, high-level application 115 communicates withLCM 116, which acts as an intermediary between high-level application 115 andLCs 117. In this manner,LCM 116 presents a single system-level interface toapplication 115. -
LCs 117 may include speech and language processing components directed to a wide variety of basic speech technologies. As previously mentioned, these speech technologies may include speech recognition, speaker identification, topic detection, and name extraction. Techniques for implementing these technologies are known in the art and will not be further described herein. -
LCM 116 provides high-level application 115 with a well-defined system state. The system state is a function of the system states ofLCs 117. FIG. 3 is a diagram that defines the state machine for the LCM system state.LCM 116 may present one of five states to high-level application 115: downstate 301, starting upstate 302, abortingstate 303, upstate 304, and shutting downstate 305. - On startup of
LCM 116, the system state defaults to downstate 301. In this state,LCs 117 are not running. High-level application 115 can interact withLCM 116 only through predefined administrative interfaces. The administrative interfaces may allow an administrator to log intoLCM 116 via, for example, a web interface or a telnet interface. With the web interface, the administrator can interact withLCM 116 through a web browser. With the telnet interface, the administrator can interact withLCM 116 through a command-line based interface. In general, the administrative interfaces allow the administrator to perform functions, such as viewing error logging information, adjusting error logging verbosity, view a current configuration file, change the LCM configuration, and interact with the LCM by posting messages. - From down
state 301,LCM 116 may receive a startup request through the administrative interfaces. In response to the startup request,LCM 116starts LCs 117 and enters starting upstate 302.LCs 117 may be started based on initialization information contained in a configuration file, called a distributed application document. When started,LCs 117 may boot-up and open a communication channel withLCM 116. If any ofLCs 117 fail to connect within a pre-specified timeout period,LCM 116 assumes a non-recoverable failure of theLC 117 and changes the system state to shutting downstate 305. - When an
LC 117 reaches a state of operational readiness (e.g., it has loaded and processed its model data), it reports its state toLCM 116.LCM 116 may respond by activating data and message connections. When all ofLCs 117 are ready,LCM 116 enters upstate 304. - Up
state 304 is the primary operational state ofLCM 116. In upstate 304,LCM 116 is responsible for managing data and message communications betweenLCs 117 and high-level application 115. While in upstate 304,LCM 116 may monitorLCs 117 for failure and switch its state to shutting downstate 305 in the event of a failure. - In shutting down
state 305,LCM 116 may discontinue data and message routing activities between the various components (i.e., LCs and high-level applications).LCM 116 may then disconnect any connected high-level applications 115 and subsequently instruct allLCs 117 to shut down. When these actions are complete,LCM 116 may enter downstate 301. - Administrators or high-
level applications 115 may issue abort requests toLCM 116 to disconnect fromLCM 116.LCM 116 may respond by entering abortingstate 303. In this state,LCM 116 deactivates message and data routing between theLCs 117 and the aborting high-level application or administrator. - By providing a centralized system state,
LCM 116 can control instabilities due to random timing problems betweenLCs 117. More particularly, becauseLCM 116 controls all communications between components insystem 200,LCM 116, in the event of an error, can shut down the components in an orderly manner and, thus, avoid system race conditions. - As previously mentioned,
LCs 117 and high-level application 115 do not communicate directly with one another. Instead, all communications inspeech system 200 are passed throughLCM 116, which defines a framework for inter-component communication. FIG. 4 is a diagram illustrating communication paths insystem 200. - As shown in FIG. 4, LC1 communicates with LCn through
LCM 116. Similarly, high-level application 115 and LC1-LCn communicate with one another throughLCM 116. A benefit of this communication framework is that it minimizes port management inside the LCs and the high-level applications, such asapplication 115. Specifically,LCs 117 and high-level applications 115 only need to communicate with one entity—LCM 116. - The LCM communication framework may provide two ways for communicating: message and data. Message communication can be conceptualized as an asynchronous remote procedure call by an initiating component to a receiving component. Message communication is generally used to initiate actions in
LCs 117. Data communication provides a way to pass data units between components, where these data units do not invoke actions in the receiving component. Instead, the data units are processed by the receiving component. - Generally, the purpose of sending messages is to invoke an action in the receiver of the message. In one implementation, messages are transmitted as serialized extensible markup language (XML) elements. The end of a message may be indicated by a zero byte (i.e. 0×00, a.k.a. NULL-termination). FIG. 5 is a diagram illustrating a
message 501 transmitted between twoLCs 117, labeled as LC1 and LC2.Message 501 is a simple message that instructs LC2 to take a particular action. -
Message 501 has a one-to-one relationship between components, i.e., there is one sender (LC1) and one receiver (LC2) of the message.LCM 116 may also support m:n message relationships, in which there can be m senders and n receivers of one particular message, where both m and n are greater than or equal to one. A message can be sent from any one of the m senders for delivery to each of the n receivers. - Table I, below, illustrates a number of possible system messages that relate to the control of
LCM 116.TABLE I Message Name Description LCM_ABORT While executing a system-abort operation, the LCM will send an <LCM_ABORT/>to every component (LCs and high-level applications), instructing them to discontinue any system-related activities, reset themselves and then report their readiness. LCM_ABORT_DONE Once a component has reacted appropriately to an abort request from the LCM, it notifies the LCM of its return to operational readiness by sending an <LCM_ABORT_DONE/>. LCM_CONNECT After a high-level application opens a socket connection to the LCM's port, it sends an <LCM_CONNECT name=””/>, identifying itself using the attribute name. LCM_CONNECT_ACK In response to an LCM_CONNECT message from a high-level application, the LCM will send an LCM_CONNECT_ACK to the high-level application. LCM_DISCONNECT The LCM sends an <LCM_DISCONNECT/> message to a high- level application to instruct the high-level application to disconnect. LCM_HELLO After an LC opens a socket connection to the LCM's port, it will send an <LCM_HELLO process-id=””/>, identifying itself via its process ID in the attribute process-id. LCM_HELLO_ACK In response to an LCM_HELLO message from an LC, the LCM will send back an LCM_HELLO_ACK. LCM_LOG This message is sent from LCs to the LCM providing text that the respective LC wishes to add to the system log. The message syntax is: <LCM_LOG level=“ . . . ” message=“ . . . ”/>, where the attri- bute level specifies the logging level, and message contains the logging text. LCM_READY An LC sends an <LCM_READY/> message to the LCM when it has reached operational readiness. LCM_SHUTDOWN The LCM will send an <LCM_SHUTDOWN/> message to an LC to instruct the LC to shut itself down. LCM_SYSTEM_ABORT A high-level application can send an <LCM_SYSTEM_ABORT/> message to the LCM to initiate a system-abort. LCM_SYSTEM_READY An <LCM_SYSTEM_READY/> will be distributed to all LCs and (potentially connected) high-level applications, when the entire system has reached a state of operational readiness, i.e. when the system state is changed to up. - Generally, the purpose of data communication between components, such as
LCs 117 and high-level applications 115, is to pass data units, such as packets, of structured information between the components. In contrast to messages, data communication does not generally invoke actions in the receiving component. Instead, the receiving component consumes or processes the information contained in the packets. - In one implementation consistent with the invention, a data pipe model is used to pass data between components. The data pipe may be a one-to-one relationship between the component that sends/produces data and the component that receives/consumes the data. A data pipe may be implemented by the producer by sending the following pieces of information to LCM116: the name of the data pipe, a data pipe command, and any arguments required by the data pipe command.
LCM 116 will then deliver the data pipe command and its arguments (if any) to the appropriate data-pipe consumer. A data pipe may be configured to connectmultiple LCs 117 in series. In this manner, data produced by a first LC may be consumed by a second LC, which may then produce a modified version of the data which may then be consumed by a third LC. - Table II, below, lists three exemplary data pipe commands.
TABLE II Com- Return-value mand Argu- (besides Command ID ments Effect error code) Clear data- 3 None Instruct the data None pipe consumer to remove any unprocessed data packets that it has in its data- receiving buffer Get number 4 None Instruct the data Unsigned of elements consumer to return the integer, in data-pipe number of data packets indicating the buffer that are currently held in number of data the data-receiving buffer. packets that are currently in the data-receiving buffer. Send data 1 Data Delivers a data packet to None packet the data-pipe consumer. The data-packet can be rejected by the data- consumer using the error code BufferFull. In this case, the data producer is responsible for retransmitting the data packet at a later time. - For a particular high-
level application 115, the choice of whichLCs 117 to use in the application and the paths for the flow of messages and data betweenLCs 117 and the high-level application 115 is controlled by a configuration document (or file) referred to herein as a distributed application document (DAD). - In one implementation, the DAD is an XML document that describes in detail the configuration of an LCM-managed system.
LCM 116 parses the DAD in determining the configuration ofspeech system 200. A particular system configuration may define the specification ofLCs 117, the specification of high-level application 115, the message and data communication connections between all the components, and error logging settings. As such, the DAD can be viewed as a complete system specification. - FIGS. 6A and 6B illustrate an
exemplary DAD 600. For ease of explanation, the DAD shown in FIG. 6 is a simplified version of a typical DAD. -
DAD 600 includes a name tag 601 that includes the name of the particular high-level application. In this example, the application is “Audio Indexer.” - Run-
time section 602 may include, during run-time, a list of all connectedLCs 117 and high-level applications 115. These run-time connections may be dynamically changed byLCM 116 as the connected components change. In this example, run-time section 602 also includes an auto-start tag that indicates thatDAD 600 is to be automatically loaded byLCM 116 whenLCM 116 is initially started. - The system specification section, located between the tags “<SYSTEM_SPECIFICATION>” (FIG. 6A) and “</SYSTEM_SPECIFICATION>” (FIG. 6B), includes a complete description of the configuration of the components in
speech system 200, including the message and data paths. As shown, the “SYSTEM_SPECIFICATION” section includes a “CONNECTION_LISTENERS” section, a “LOGGING_TARGETS” section, a “MESSAGES” section, a “DATA_PIPES” section (FIG. 6B), a “REMOTE_APPLICATIONS” section (FIG. 6B), and a “LANGUAGE_COMPONENTS” section (FIG. 6B). Each of these sections is illustrated in FIG. 6 by corresponding XML tags in which brackets (“< . . . >”) denote the beginning of a section and brackets with a slash (“</ . . . >”) denote the end of a section. - The CONNECTION_LISTENERS section includes a number of CONNECTION_LISTENER tags that define the low-level connections between the components, including the port of
LCM 116 with which the components connect. Additionally, these tags may also define whether each port is a port dedicated to a data producer, data consumer, or message. - The LOGGING_TARGETS section defines error logging settings for the system, such as target file names. Additionally, the level of detail to which errors are logged can be set in this section through the verbosity setting. Valid values for the verbosity setting according to one implementation consistent with the invention are shown in Table III.
TABLE III Logging Level Description None No logging information. Error Indicates a severe exception condition in the LC. This condition often leads to component failure and hence to system shutdown. Warning Unexpected exception-like condition. The LC can avoid failure but this is still a severe exception. Info Provides high-level component state information that might be of general interest. Detail Provide very fine-grain detailed information about the component's system state. This type of information is typically useful for component debugging. - The MESSAGES section defines the possible flow of messages between the components in
speech system 200. The MESSAGES section may include three subsections: “PUBLIC_IN”, “PUBLIC_OUT”, and “PRIVATE.” PUBLIC_IN refers to messages generated by high-level application 115 and transmitted toLCM 116. PUBLIC_OUT refers to messages fromLCM 116 and transmitted to high-level applications 115. PRIVATE refers to messages transmitted betweenLCs 117 viaLCM 116. - Exemplary message definitions are illustrated for the PUBLIC_OUT subsection of MESSAGES. Messages in PUBLIC_IN and PRIVATE may be implemented similarly. Each
entry 604 in the PUBLIC_OUT sub-section includes a message name (“message name” field), the name of the LC from which the message originates (“from” field), and the name of the destination high-level application (“to”) field. In this example, the messages are all destined for the application “decode.” The messages named “passage” and “gap” originate from the LCs identified as “spk_segment.” The message named “word” originates from the LC named “nbscore.” In operation, the LC named “nbscore” may transmit a message to the LCM that includes the label “word.”LCM 116, based onDAD 600, knows that this message should be forwarded to the high-level application “decode.” - The DATA_PIPES section defines the possible flow of data between the components in
system 200. As with the MESSAGES section, the DATA_PIPES section may include the three sub-sections PUBLIC_IN, PUBLIC_OUT, and PRIVATE. These sections similarly define data pipes between high-level applications 115 andLCM 116, betweenLCM 116 and the high-level applications, and between LCs, respectively. - Two exemplary data pipe entries are shown in
DAD 600 under the PRIVATE sub-section of DATA_PIPES. The first data pipe entry is named “phn2seq.” This data pipe is received byLCM 116 from the LC “filter_component” and forwarded to the LC “speaker_seg.” The second data pipe entry is named “seg2fw.” Data transmitted through this data pipe is received byLCM 116 from the LC “speaker_seg” and forwarded to the LC “decoder_fw.” - The “REMOTE_APPLICATIONS” section defines high-
level applications 115 that connect toLCM 116. One remote application, named “feed_audio” is illustrated as being defined in this section. - The “LANGUAGE_COMPONENTS” section defines
LCs 117 that may communicate withLCM 116. OneLC 117, named “decoder_phn” is defined in this section. - FIG. 7 is a diagram illustrating components in an exemplary speech application. The speech application shown in FIG. 7 may be a dialog manager that recognizes speech received over a telephone connection and takes action based on the instructions from the telephone caller.
- High-
level application 701 may include a dialog manager application that responds to speech-based commands from the caller and generates appropriate responses for the caller. The speech processing used to recognize the commands in the speech is primarily performed by LCs 703-707. LCs 703-707 include DTMF (dual-tone multi-frequency)recognizer component 703, voice-over-IP (VoIP)component 704,speech segmenter component 705, text-to-speech component 706, andspeech recognizer component 707. -
DTMF component 703 is configured to recognize key presses on a touch-tone telephone based on the corresponding DTMF signal generated by the telephone.VoIP component 704 receives the user's telephone call. In this example, the telephone call is received as a packetized signal in a VoIP connection.Speech segmenter component 705 segments speech signals into useful segments.Speech segmenter component 705 may, for example, segment input speech signals into audio segments corresponding to individual words or sentences. Text-to-speech component 706 may generate synthesized speech signals based on input text documents.Speech recognizer component 707 performs basic speech recognition of input speech signals. -
LCM 702 acts as an intermediary between high-level application 701 and LCs 703-707.LCM 702 reads a DAD document to determine the message and data interactions between high-level application 701 and LCs 703-707. For example, the DAD may dictate that speech received atVoIP component 704 is to be transmitted via a data pipe tospeech segmenter component 705. The output ofspeech segmenter component 705 may be forwarded tospeech recognizer component 707, the output of which may then be forwarded to high-level application 701. Similarly, high-level application 701 may respond to callers by generating text that it transmits, viaLCM 702, to text-to-speech component 706. The synthesized text output from text-to-speech component 706 may then be transmitted toVoIP component 704 for transmission to the caller. In each of these instances of data transfer, the data is transmitted through and routed byLCM 702. - An LCM, as described above, functions as middleware between one or more language and technology components and one or more high-level applications. In aggregate, the LCM, the language and technology component(s), and the high-level application(s) form a speech system. The components of the speech system may be distributed. All data and messages in the speech system pass through the LCM. A configuration file defines relationships, such as message and data paths, for the speech system.
- The foregoing description of preferred embodiments of the invention provides illustration and description, but is not intended to be exhaustive or to limit the invention to the precise form disclosed. Modifications and variations are possible in light of the above teachings or may be acquired from practice of the invention.
- Certain portions of the invention have been described as software that performs one or more functions. The software may more generally be implemented as any type of logic. This logic may include hardware, such as application specific integrated circuit or a field programmable gate array, software, or a combination of hardware and software.
- No element, act, or instruction used in the description of the present application should be construed as critical or essential to the invention unless explicitly described as such. Also, as used herein, the article “a” is intended to include one or more items. Where only one item is intended, the term “one” or similar language is used.
- The scope of the invention is defined by the claims and their equivalents.
Claims (29)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US10/685,403 US20040083090A1 (en) | 2002-10-17 | 2003-10-16 | Manager for integrating language technology components |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US41921402P | 2002-10-17 | 2002-10-17 | |
US10/685,403 US20040083090A1 (en) | 2002-10-17 | 2003-10-16 | Manager for integrating language technology components |
Publications (1)
Publication Number | Publication Date |
---|---|
US20040083090A1 true US20040083090A1 (en) | 2004-04-29 |
Family
ID=32110223
Family Applications (9)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US10/685,479 Abandoned US20040163034A1 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for labeling clusters of documents |
US10/685,478 Abandoned US20040083104A1 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for providing interactive speaker identification training |
US10/685,445 Abandoned US20040138894A1 (en) | 2002-10-17 | 2003-10-16 | Speech transcription tool for efficient speech transcription |
US10/685,410 Expired - Fee Related US7389229B2 (en) | 2002-10-17 | 2003-10-16 | Unified clustering tree |
US10/685,585 Active 2026-01-10 US7424427B2 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for classifying audio into broad phoneme classes |
US10/685,586 Abandoned US20040204939A1 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for speaker change detection |
US10/685,403 Abandoned US20040083090A1 (en) | 2002-10-17 | 2003-10-16 | Manager for integrating language technology components |
US10/685,565 Active - Reinstated 2026-04-05 US7292977B2 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for providing online fast speaker adaptation in speech recognition |
US10/685,566 Abandoned US20040176946A1 (en) | 2002-10-17 | 2003-10-16 | Pronunciation symbols based on the orthographic lexicon of a language |
Family Applications Before (6)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US10/685,479 Abandoned US20040163034A1 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for labeling clusters of documents |
US10/685,478 Abandoned US20040083104A1 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for providing interactive speaker identification training |
US10/685,445 Abandoned US20040138894A1 (en) | 2002-10-17 | 2003-10-16 | Speech transcription tool for efficient speech transcription |
US10/685,410 Expired - Fee Related US7389229B2 (en) | 2002-10-17 | 2003-10-16 | Unified clustering tree |
US10/685,585 Active 2026-01-10 US7424427B2 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for classifying audio into broad phoneme classes |
US10/685,586 Abandoned US20040204939A1 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for speaker change detection |
Family Applications After (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US10/685,565 Active - Reinstated 2026-04-05 US7292977B2 (en) | 2002-10-17 | 2003-10-16 | Systems and methods for providing online fast speaker adaptation in speech recognition |
US10/685,566 Abandoned US20040176946A1 (en) | 2002-10-17 | 2003-10-16 | Pronunciation symbols based on the orthographic lexicon of a language |
Country Status (1)
Country | Link |
---|---|
US (9) | US20040163034A1 (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120109638A1 (en) * | 2010-10-27 | 2012-05-03 | Hon Hai Precision Industry Co., Ltd. | Electronic device and method for extracting component names using the same |
Families Citing this family (167)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7763189B2 (en) * | 2001-05-16 | 2010-07-27 | E. I. Du Pont De Nemours And Company | Dielectric composition with reduced resistance |
ATE508455T1 (en) * | 2002-09-27 | 2011-05-15 | Callminer Inc | METHOD FOR STATISTICALLY ANALYZING LANGUAGE |
WO2004090870A1 (en) * | 2003-04-04 | 2004-10-21 | Kabushiki Kaisha Toshiba | Method and apparatus for encoding or decoding wide-band audio |
US7567908B2 (en) * | 2004-01-13 | 2009-07-28 | International Business Machines Corporation | Differential dynamic content delivery with text display in dependence upon simultaneous speech |
JP2005202014A (en) * | 2004-01-14 | 2005-07-28 | Sony Corp | Audio signal processor, audio signal processing method, and audio signal processing program |
US8923838B1 (en) | 2004-08-19 | 2014-12-30 | Nuance Communications, Inc. | System, method and computer program product for activating a cellular phone account |
JP4220449B2 (en) * | 2004-09-16 | 2009-02-04 | 株式会社東芝 | Indexing device, indexing method, and indexing program |
US7956905B2 (en) * | 2005-02-28 | 2011-06-07 | Fujifilm Corporation | Titling apparatus, a titling method, and a machine readable medium storing thereon a computer program for titling |
GB0511307D0 (en) * | 2005-06-03 | 2005-07-13 | South Manchester University Ho | A method for generating output data |
US7382933B2 (en) * | 2005-08-24 | 2008-06-03 | International Business Machines Corporation | System and method for semantic video segmentation based on joint audiovisual and text analysis |
WO2007023436A1 (en) | 2005-08-26 | 2007-03-01 | Koninklijke Philips Electronics N.V. | System and method for synchronizing sound and manually transcribed text |
US7801893B2 (en) * | 2005-09-30 | 2010-09-21 | Iac Search & Media, Inc. | Similarity detection and clustering of images |
US20070094023A1 (en) * | 2005-10-21 | 2007-04-26 | Callminer, Inc. | Method and apparatus for processing heterogeneous units of work |
US20070094270A1 (en) * | 2005-10-21 | 2007-04-26 | Callminer, Inc. | Method and apparatus for the processing of heterogeneous units of work |
US8756057B2 (en) | 2005-11-02 | 2014-06-17 | Nuance Communications, Inc. | System and method using feedback speech analysis for improving speaking ability |
KR100755677B1 (en) * | 2005-11-02 | 2007-09-05 | 삼성전자주식회사 | Apparatus and method for dialogue speech recognition using topic detection |
US7503724B2 (en) * | 2005-11-18 | 2009-03-17 | Blacklidge Emulsions, Inc. | Method for bonding prepared substrates for roadways using a low-tracking asphalt emulsion coating |
US20070129943A1 (en) * | 2005-12-06 | 2007-06-07 | Microsoft Corporation | Speech recognition using adaptation and prior knowledge |
CA2536976A1 (en) * | 2006-02-20 | 2007-08-20 | Diaphonics, Inc. | Method and apparatus for detecting speaker change in a voice transaction |
US8996592B2 (en) * | 2006-06-26 | 2015-03-31 | Scenera Technologies, Llc | Methods, systems, and computer program products for identifying a container associated with a plurality of files |
US20080004876A1 (en) * | 2006-06-30 | 2008-01-03 | Chuang He | Non-enrolled continuous dictation |
US20080051916A1 (en) * | 2006-08-28 | 2008-02-28 | Arcadyan Technology Corporation | Method and apparatus for recording streamed audio |
KR100826875B1 (en) * | 2006-09-08 | 2008-05-06 | 한국전자통신연구원 | On-line speaker recognition method and apparatus for thereof |
US8073681B2 (en) | 2006-10-16 | 2011-12-06 | Voicebox Technologies, Inc. | System and method for a cooperative conversational voice user interface |
US20080104066A1 (en) * | 2006-10-27 | 2008-05-01 | Yahoo! Inc. | Validating segmentation criteria |
US7272558B1 (en) | 2006-12-01 | 2007-09-18 | Coveo Solutions Inc. | Speech recognition training method for audio and video file indexing on a search engine |
US20080154579A1 (en) * | 2006-12-21 | 2008-06-26 | Krishna Kummamuru | Method of analyzing conversational transcripts |
US7818176B2 (en) | 2007-02-06 | 2010-10-19 | Voicebox Technologies, Inc. | System and method for selecting and presenting advertisements based on natural language processing of voice-based input |
WO2008137616A1 (en) * | 2007-05-04 | 2008-11-13 | Nuance Communications, Inc. | Multi-class constrained maximum likelihood linear regression |
WO2009018223A1 (en) * | 2007-07-27 | 2009-02-05 | Sparkip, Inc. | System and methods for clustering large database of documents |
DE602007004733D1 (en) * | 2007-10-10 | 2010-03-25 | Harman Becker Automotive Sys | speaker recognition |
JP4405542B2 (en) * | 2007-10-24 | 2010-01-27 | 株式会社東芝 | Apparatus, method and program for clustering phoneme models |
US9386154B2 (en) | 2007-12-21 | 2016-07-05 | Nuance Communications, Inc. | System, method and software program for enabling communications between customer service agents and users of communication devices |
JPWO2009122779A1 (en) * | 2008-04-03 | 2011-07-28 | 日本電気株式会社 | Text data processing apparatus, method and program |
US9305548B2 (en) | 2008-05-27 | 2016-04-05 | Voicebox Technologies Corporation | System and method for an integrated, multi-modal, multi-device natural language voice services environment |
US9020816B2 (en) * | 2008-08-14 | 2015-04-28 | 21Ct, Inc. | Hidden markov model for speech processing with training method |
CA2680304C (en) * | 2008-09-25 | 2017-08-22 | Multimodal Technologies, Inc. | Decoding-time prediction of non-verbalized tokens |
US8458105B2 (en) | 2009-02-12 | 2013-06-04 | Decisive Analytics Corporation | Method and apparatus for analyzing and interrelating data |
US8326637B2 (en) | 2009-02-20 | 2012-12-04 | Voicebox Technologies, Inc. | System and method for processing multi-modal device interactions in a natural language voice services environment |
US8301446B2 (en) * | 2009-03-30 | 2012-10-30 | Adacel Systems, Inc. | System and method for training an acoustic model with reduced feature space variation |
US8412525B2 (en) * | 2009-04-30 | 2013-04-02 | Microsoft Corporation | Noise robust speech classifier ensemble |
US8713018B2 (en) | 2009-07-28 | 2014-04-29 | Fti Consulting, Inc. | System and method for displaying relationships between electronically stored information to provide classification suggestions via inclusion |
CA3026879A1 (en) | 2009-08-24 | 2011-03-10 | Nuix North America, Inc. | Generating a reference set for use during document review |
US8554562B2 (en) * | 2009-11-15 | 2013-10-08 | Nuance Communications, Inc. | Method and system for speaker diarization |
US8983958B2 (en) * | 2009-12-21 | 2015-03-17 | Business Objects Software Limited | Document indexing based on categorization and prioritization |
JP5477635B2 (en) * | 2010-02-15 | 2014-04-23 | ソニー株式会社 | Information processing apparatus and method, and program |
US10273637B2 (en) | 2010-02-24 | 2019-04-30 | Blacklidge Emulsions, Inc. | Hot applied tack coat |
US9305553B2 (en) * | 2010-04-28 | 2016-04-05 | William S. Meisel | Speech recognition accuracy improvement through speaker categories |
US9009040B2 (en) * | 2010-05-05 | 2015-04-14 | Cisco Technology, Inc. | Training a transcription system |
US8391464B1 (en) | 2010-06-24 | 2013-03-05 | Nuance Communications, Inc. | Customer service system, method, and software program product for responding to queries using natural language understanding |
JP2012038131A (en) * | 2010-08-09 | 2012-02-23 | Sony Corp | Information processing unit, information processing method, and program |
US8630854B2 (en) * | 2010-08-31 | 2014-01-14 | Fujitsu Limited | System and method for generating videoconference transcriptions |
US20120084149A1 (en) * | 2010-09-10 | 2012-04-05 | Paolo Gaudiano | Methods and systems for online advertising with interactive text clouds |
US8791977B2 (en) | 2010-10-05 | 2014-07-29 | Fujitsu Limited | Method and system for presenting metadata during a videoconference |
KR101172663B1 (en) * | 2010-12-31 | 2012-08-08 | 엘지전자 주식회사 | Mobile terminal and method for grouping application thereof |
US20120197643A1 (en) * | 2011-01-27 | 2012-08-02 | General Motors Llc | Mapping obstruent speech energy to lower frequencies |
GB2489489B (en) * | 2011-03-30 | 2013-08-21 | Toshiba Res Europ Ltd | A speech processing system and method |
US9774747B2 (en) * | 2011-04-29 | 2017-09-26 | Nexidia Inc. | Transcription system |
US8612447B2 (en) * | 2011-06-22 | 2013-12-17 | Rogers Communications Inc. | Systems and methods for ranking document clusters |
US9313336B2 (en) | 2011-07-21 | 2016-04-12 | Nuance Communications, Inc. | Systems and methods for processing audio signals captured using microphones of multiple devices |
JP2013025299A (en) * | 2011-07-26 | 2013-02-04 | Toshiba Corp | Transcription support system and transcription support method |
JP5638479B2 (en) * | 2011-07-26 | 2014-12-10 | 株式会社東芝 | Transcription support system and transcription support method |
JP5404726B2 (en) * | 2011-09-26 | 2014-02-05 | 株式会社東芝 | Information processing apparatus, information processing method, and program |
US8433577B2 (en) | 2011-09-27 | 2013-04-30 | Google Inc. | Detection of creative works on broadcast media |
US20130144414A1 (en) * | 2011-12-06 | 2013-06-06 | Cisco Technology, Inc. | Method and apparatus for discovering and labeling speakers in a large and growing collection of videos with minimal user effort |
US9002848B1 (en) * | 2011-12-27 | 2015-04-07 | Google Inc. | Automatic incremental labeling of document clusters |
JP2013161205A (en) * | 2012-02-03 | 2013-08-19 | Sony Corp | Information processing device, information processing method and program |
US20130266127A1 (en) | 2012-04-10 | 2013-10-10 | Raytheon Bbn Technologies Corp | System and method for removing sensitive data from a recording |
US20140365221A1 (en) * | 2012-07-31 | 2014-12-11 | Novospeech Ltd. | Method and apparatus for speech recognition |
US8676590B1 (en) | 2012-09-26 | 2014-03-18 | Google Inc. | Web-based audio transcription tool |
US20140136204A1 (en) * | 2012-11-13 | 2014-05-15 | GM Global Technology Operations LLC | Methods and systems for speech systems |
US20140207786A1 (en) * | 2013-01-22 | 2014-07-24 | Equivio Ltd. | System and methods for computerized information governance of electronic documents |
US9865266B2 (en) * | 2013-02-25 | 2018-01-09 | Nuance Communications, Inc. | Method and apparatus for automated speaker parameters adaptation in a deployed speaker verification system |
US9330167B1 (en) * | 2013-05-13 | 2016-05-03 | Groupon, Inc. | Method, apparatus, and computer program product for classification and tagging of textual data |
US10736529B2 (en) | 2013-09-25 | 2020-08-11 | Bardy Diagnostics, Inc. | Subcutaneous insertable electrocardiography monitor |
US10433751B2 (en) | 2013-09-25 | 2019-10-08 | Bardy Diagnostics, Inc. | System and method for facilitating a cardiac rhythm disorder diagnosis based on subcutaneous cardiac monitoring data |
US9717432B2 (en) | 2013-09-25 | 2017-08-01 | Bardy Diagnostics, Inc. | Extended wear electrocardiography patch using interlaced wire electrodes |
US9619660B1 (en) | 2013-09-25 | 2017-04-11 | Bardy Diagnostics, Inc. | Computer-implemented system for secure physiological data collection and processing |
US10251576B2 (en) | 2013-09-25 | 2019-04-09 | Bardy Diagnostics, Inc. | System and method for ECG data classification for use in facilitating diagnosis of cardiac rhythm disorders with the aid of a digital computer |
US9615763B2 (en) | 2013-09-25 | 2017-04-11 | Bardy Diagnostics, Inc. | Ambulatory electrocardiography monitor recorder optimized for capturing low amplitude cardiac action potential propagation |
US9700227B2 (en) | 2013-09-25 | 2017-07-11 | Bardy Diagnostics, Inc. | Ambulatory electrocardiography monitoring patch optimized for capturing low amplitude cardiac action potential propagation |
US9545204B2 (en) | 2013-09-25 | 2017-01-17 | Bardy Diagnostics, Inc. | Extended wear electrocardiography patch |
US10624551B2 (en) | 2013-09-25 | 2020-04-21 | Bardy Diagnostics, Inc. | Insertable cardiac monitor for use in performing long term electrocardiographic monitoring |
US9408551B2 (en) | 2013-11-14 | 2016-08-09 | Bardy Diagnostics, Inc. | System and method for facilitating diagnosis of cardiac rhythm disorders with the aid of a digital computer |
US10736531B2 (en) | 2013-09-25 | 2020-08-11 | Bardy Diagnostics, Inc. | Subcutaneous insertable cardiac monitor optimized for long term, low amplitude electrocardiographic data collection |
US20190167139A1 (en) | 2017-12-05 | 2019-06-06 | Gust H. Bardy | Subcutaneous P-Wave Centric Insertable Cardiac Monitor For Long Term Electrocardiographic Monitoring |
US10820801B2 (en) | 2013-09-25 | 2020-11-03 | Bardy Diagnostics, Inc. | Electrocardiography monitor configured for self-optimizing ECG data compression |
US11213237B2 (en) | 2013-09-25 | 2022-01-04 | Bardy Diagnostics, Inc. | System and method for secure cloud-based physiological data processing and delivery |
US9408545B2 (en) | 2013-09-25 | 2016-08-09 | Bardy Diagnostics, Inc. | Method for efficiently encoding and compressing ECG data optimized for use in an ambulatory ECG monitor |
US9504423B1 (en) | 2015-10-05 | 2016-11-29 | Bardy Diagnostics, Inc. | Method for addressing medical conditions through a wearable health monitor with the aid of a digital computer |
US9364155B2 (en) | 2013-09-25 | 2016-06-14 | Bardy Diagnostics, Inc. | Self-contained personal air flow sensing monitor |
US9655537B2 (en) | 2013-09-25 | 2017-05-23 | Bardy Diagnostics, Inc. | Wearable electrocardiography and physiology monitoring ensemble |
US10888239B2 (en) | 2013-09-25 | 2021-01-12 | Bardy Diagnostics, Inc. | Remote interfacing electrocardiography patch |
US10806360B2 (en) | 2013-09-25 | 2020-10-20 | Bardy Diagnostics, Inc. | Extended wear ambulatory electrocardiography and physiological sensor monitor |
US9345414B1 (en) | 2013-09-25 | 2016-05-24 | Bardy Diagnostics, Inc. | Method for providing dynamic gain over electrocardiographic data with the aid of a digital computer |
US11723575B2 (en) | 2013-09-25 | 2023-08-15 | Bardy Diagnostics, Inc. | Electrocardiography patch |
US9655538B2 (en) | 2013-09-25 | 2017-05-23 | Bardy Diagnostics, Inc. | Self-authenticating electrocardiography monitoring circuit |
US9717433B2 (en) | 2013-09-25 | 2017-08-01 | Bardy Diagnostics, Inc. | Ambulatory electrocardiography monitoring patch optimized for capturing low amplitude cardiac action potential propagation |
US10667711B1 (en) | 2013-09-25 | 2020-06-02 | Bardy Diagnostics, Inc. | Contact-activated extended wear electrocardiography and physiological sensor monitor recorder |
US10463269B2 (en) | 2013-09-25 | 2019-11-05 | Bardy Diagnostics, Inc. | System and method for machine-learning-based atrial fibrillation detection |
US9775536B2 (en) | 2013-09-25 | 2017-10-03 | Bardy Diagnostics, Inc. | Method for constructing a stress-pliant physiological electrode assembly |
US9433367B2 (en) | 2013-09-25 | 2016-09-06 | Bardy Diagnostics, Inc. | Remote interfacing of extended wear electrocardiography and physiological sensor monitor |
US10433748B2 (en) | 2013-09-25 | 2019-10-08 | Bardy Diagnostics, Inc. | Extended wear electrocardiography and physiological sensor monitor |
US10799137B2 (en) | 2013-09-25 | 2020-10-13 | Bardy Diagnostics, Inc. | System and method for facilitating a cardiac rhythm disorder diagnosis with the aid of a digital computer |
WO2015048194A1 (en) | 2013-09-25 | 2015-04-02 | Bardy Diagnostics, Inc. | Self-contained personal air flow sensing monitor |
US9737224B2 (en) | 2013-09-25 | 2017-08-22 | Bardy Diagnostics, Inc. | Event alerting through actigraphy embedded within electrocardiographic data |
US20150100582A1 (en) * | 2013-10-08 | 2015-04-09 | Cisco Technology, Inc. | Association of topic labels with digital content |
US9495439B2 (en) * | 2013-10-08 | 2016-11-15 | Cisco Technology, Inc. | Organizing multimedia content |
US9942396B2 (en) * | 2013-11-01 | 2018-04-10 | Adobe Systems Incorporated | Document distribution and interaction |
DE102013224417B3 (en) * | 2013-11-28 | 2015-05-07 | Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. | Hearing aid with basic frequency modification, method for processing a speech signal and computer program with a program code for performing the method |
CN104143326B (en) * | 2013-12-03 | 2016-11-02 | 腾讯科技(深圳)有限公司 | A kind of voice command identification method and device |
US9544149B2 (en) | 2013-12-16 | 2017-01-10 | Adobe Systems Incorporated | Automatic E-signatures in response to conditions and/or events |
WO2015105994A1 (en) | 2014-01-08 | 2015-07-16 | Callminer, Inc. | Real-time conversational analytics facility |
JP6392012B2 (en) * | 2014-07-14 | 2018-09-19 | 株式会社東芝 | Speech synthesis dictionary creation device, speech synthesis device, speech synthesis dictionary creation method, and speech synthesis dictionary creation program |
US9728190B2 (en) * | 2014-07-25 | 2017-08-08 | International Business Machines Corporation | Summarization of audio data |
EP3195145A4 (en) | 2014-09-16 | 2018-01-24 | VoiceBox Technologies Corporation | Voice commerce |
US9703982B2 (en) | 2014-11-06 | 2017-07-11 | Adobe Systems Incorporated | Document distribution and interaction |
US9531545B2 (en) | 2014-11-24 | 2016-12-27 | Adobe Systems Incorporated | Tracking and notification of fulfillment events |
US9432368B1 (en) | 2015-02-19 | 2016-08-30 | Adobe Systems Incorporated | Document distribution and interaction |
JP6464411B6 (en) * | 2015-02-25 | 2019-03-13 | Dynabook株式会社 | Electronic device, method and program |
US10447646B2 (en) * | 2015-06-15 | 2019-10-15 | International Business Machines Corporation | Online communication modeling and analysis |
US10068445B2 (en) | 2015-06-24 | 2018-09-04 | Google Llc | Systems and methods of home-specific sound event detection |
US10089061B2 (en) * | 2015-08-28 | 2018-10-02 | Kabushiki Kaisha Toshiba | Electronic device and method |
US9935777B2 (en) | 2015-08-31 | 2018-04-03 | Adobe Systems Incorporated | Electronic signature framework with enhanced security |
US20170075652A1 (en) | 2015-09-14 | 2017-03-16 | Kabushiki Kaisha Toshiba | Electronic device and method |
US9626653B2 (en) | 2015-09-21 | 2017-04-18 | Adobe Systems Incorporated | Document distribution and interaction with delegation of signature authority |
US9754593B2 (en) * | 2015-11-04 | 2017-09-05 | International Business Machines Corporation | Sound envelope deconstruction to identify words and speakers in continuous speech |
EP3389477B1 (en) | 2015-12-16 | 2023-05-10 | Dolby Laboratories Licensing Corporation | Suppression of breath in audio signals |
US10347215B2 (en) | 2016-05-27 | 2019-07-09 | Adobe Inc. | Multi-device electronic signature framework |
AU2017274558B2 (en) | 2016-06-02 | 2021-11-11 | Nuix North America Inc. | Analyzing clusters of coded documents |
US10255905B2 (en) * | 2016-06-10 | 2019-04-09 | Google Llc | Predicting pronunciations with word stress |
US10217453B2 (en) | 2016-10-14 | 2019-02-26 | Soundhound, Inc. | Virtual assistant configured by selection of wake-up phrase |
US20180232623A1 (en) * | 2017-02-10 | 2018-08-16 | International Business Machines Corporation | Techniques for answering questions based on semantic distances between subjects |
US10503919B2 (en) | 2017-04-10 | 2019-12-10 | Adobe Inc. | Electronic signature framework with keystroke biometric authentication |
US20180336892A1 (en) * | 2017-05-16 | 2018-11-22 | Apple Inc. | Detecting a trigger of a digital assistant |
GB2578386B (en) | 2017-06-27 | 2021-12-01 | Cirrus Logic Int Semiconductor Ltd | Detection of replay attack |
GB2563953A (en) | 2017-06-28 | 2019-01-02 | Cirrus Logic Int Semiconductor Ltd | Detection of replay attack |
GB201713697D0 (en) | 2017-06-28 | 2017-10-11 | Cirrus Logic Int Semiconductor Ltd | Magnetic detection of replay attack |
GB201801526D0 (en) | 2017-07-07 | 2018-03-14 | Cirrus Logic Int Semiconductor Ltd | Methods, apparatus and systems for authentication |
GB201801532D0 (en) | 2017-07-07 | 2018-03-14 | Cirrus Logic Int Semiconductor Ltd | Methods, apparatus and systems for audio playback |
GB201801528D0 (en) | 2017-07-07 | 2018-03-14 | Cirrus Logic Int Semiconductor Ltd | Method, apparatus and systems for biometric processes |
GB201801527D0 (en) | 2017-07-07 | 2018-03-14 | Cirrus Logic Int Semiconductor Ltd | Method, apparatus and systems for biometric processes |
GB201801664D0 (en) | 2017-10-13 | 2018-03-21 | Cirrus Logic Int Semiconductor Ltd | Detection of liveness |
GB201804843D0 (en) | 2017-11-14 | 2018-05-09 | Cirrus Logic Int Semiconductor Ltd | Detection of replay attack |
GB2567503A (en) * | 2017-10-13 | 2019-04-17 | Cirrus Logic Int Semiconductor Ltd | Analysing speech signals |
GB201801661D0 (en) | 2017-10-13 | 2018-03-21 | Cirrus Logic International Uk Ltd | Detection of liveness |
GB201801659D0 (en) | 2017-11-14 | 2018-03-21 | Cirrus Logic Int Semiconductor Ltd | Detection of loudspeaker playback |
TWI625680B (en) | 2017-12-15 | 2018-06-01 | 財團法人工業技術研究院 | Method and device for recognizing facial expressions |
US11264037B2 (en) | 2018-01-23 | 2022-03-01 | Cirrus Logic, Inc. | Speaker identification |
US11735189B2 (en) | 2018-01-23 | 2023-08-22 | Cirrus Logic, Inc. | Speaker identification |
US11475899B2 (en) | 2018-01-23 | 2022-10-18 | Cirrus Logic, Inc. | Speaker identification |
CN109300486B (en) * | 2018-07-30 | 2021-06-25 | 四川大学 | PICGTFs and SSMC enhanced cleft palate speech pharynx fricative automatic identification method |
US10692490B2 (en) | 2018-07-31 | 2020-06-23 | Cirrus Logic, Inc. | Detection of replay attack |
JP7007617B2 (en) * | 2018-08-15 | 2022-01-24 | 日本電信電話株式会社 | End-of-speech judgment device, end-of-speech judgment method and program |
US10915614B2 (en) | 2018-08-31 | 2021-02-09 | Cirrus Logic, Inc. | Biometric authentication |
US11037574B2 (en) | 2018-09-05 | 2021-06-15 | Cirrus Logic, Inc. | Speaker recognition and speaker change detection |
US11116451B2 (en) | 2019-07-03 | 2021-09-14 | Bardy Diagnostics, Inc. | Subcutaneous P-wave centric insertable cardiac monitor with energy harvesting capabilities |
US11096579B2 (en) | 2019-07-03 | 2021-08-24 | Bardy Diagnostics, Inc. | System and method for remote ECG data streaming in real-time |
US11696681B2 (en) | 2019-07-03 | 2023-07-11 | Bardy Diagnostics Inc. | Configurable hardware platform for physiological monitoring of a living body |
US11410642B2 (en) * | 2019-08-16 | 2022-08-09 | Soundhound, Inc. | Method and system using phoneme embedding |
US11354920B2 (en) | 2019-10-12 | 2022-06-07 | International Business Machines Corporation | Updating and implementing a document from an audio proceeding |
US11404049B2 (en) * | 2019-12-09 | 2022-08-02 | Microsoft Technology Licensing, Llc | Interactive augmentation and integration of real-time speech-to-text |
US11862168B1 (en) * | 2020-03-30 | 2024-01-02 | Amazon Technologies, Inc. | Speaker disambiguation and transcription from multiple audio feeds |
US11373657B2 (en) * | 2020-05-01 | 2022-06-28 | Raytheon Applied Signal Technology, Inc. | System and method for speaker identification in audio data |
US11875791B2 (en) * | 2020-05-21 | 2024-01-16 | Orcam Technologies Ltd. | Systems and methods for emphasizing a user's name |
US11315545B2 (en) | 2020-07-09 | 2022-04-26 | Raytheon Applied Signal Technology, Inc. | System and method for language identification in audio data |
CN113284508B (en) * | 2021-07-21 | 2021-11-09 | 中国科学院自动化研究所 | Hierarchical differentiation based generated audio detection system |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6931376B2 (en) * | 2000-07-20 | 2005-08-16 | Microsoft Corporation | Speech-related event notification system |
Family Cites Families (125)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
AUPQ131399A0 (en) * | 1999-06-30 | 1999-07-22 | Silverbrook Research Pty Ltd | A method and apparatus (NPAGE02) |
US4908866A (en) * | 1985-02-04 | 1990-03-13 | Eric Goldwasser | Speech transcribing system |
JPH0693221B2 (en) | 1985-06-12 | 1994-11-16 | 株式会社日立製作所 | Voice input device |
US4879648A (en) * | 1986-09-19 | 1989-11-07 | Nancy P. Cochran | Search system which continuously displays search terms during scrolling and selections of individually displayed data sets |
US4908868A (en) * | 1989-02-21 | 1990-03-13 | Mctaggart James E | Phase polarity test instrument and method |
US6978277B2 (en) * | 1989-10-26 | 2005-12-20 | Encyclopaedia Britannica, Inc. | Multimedia search system |
US5418716A (en) * | 1990-07-26 | 1995-05-23 | Nec Corporation | System for recognizing sentence patterns and a system for recognizing sentence patterns and grammatical cases |
US5404295A (en) * | 1990-08-16 | 1995-04-04 | Katz; Boris | Method and apparatus for utilizing annotations to facilitate computer retrieval of database material |
US5317732A (en) * | 1991-04-26 | 1994-05-31 | Commodore Electronics Limited | System for relocating a multimedia presentation on a different platform by extracting a resource map in order to remap and relocate resources |
US5875108A (en) * | 1991-12-23 | 1999-02-23 | Hoffberg; Steven M. | Ergonomic man-machine interface incorporating adaptive pattern recognition based control system |
US5544257A (en) * | 1992-01-08 | 1996-08-06 | International Business Machines Corporation | Continuous parameter hidden Markov model approach to automatic handwriting recognition |
JP2524472B2 (en) * | 1992-09-21 | 1996-08-14 | インターナショナル・ビジネス・マシーンズ・コーポレイション | How to train a telephone line based speech recognition system |
CA2108536C (en) * | 1992-11-24 | 2000-04-04 | Oscar Ernesto Agazzi | Text recognition using two-dimensional stochastic models |
US5689641A (en) * | 1993-10-01 | 1997-11-18 | Vicor, Inc. | Multimedia collaboration system arrangement for routing compressed AV signal through a participant site without decompressing the AV signal |
JP3185505B2 (en) | 1993-12-24 | 2001-07-11 | 株式会社日立製作所 | Meeting record creation support device |
GB2285895A (en) | 1994-01-19 | 1995-07-26 | Ibm | Audio conferencing system which generates a set of minutes |
JPH07319917A (en) * | 1994-05-24 | 1995-12-08 | Fuji Xerox Co Ltd | Document data base managing device and document data base system |
US5613032A (en) * | 1994-09-02 | 1997-03-18 | Bell Communications Research, Inc. | System and method for recording, playing back and searching multimedia events wherein video, audio and text can be searched and retrieved |
WO1996010799A1 (en) | 1994-09-30 | 1996-04-11 | Motorola Inc. | Method and system for extracting features from handwritten text |
US5831615A (en) * | 1994-09-30 | 1998-11-03 | Intel Corporation | Method and apparatus for redrawing transparent windows |
US5777614A (en) * | 1994-10-14 | 1998-07-07 | Hitachi, Ltd. | Editing support system including an interactive interface |
US5835667A (en) * | 1994-10-14 | 1998-11-10 | Carnegie Mellon University | Method and apparatus for creating a searchable digital video library and a system and method of using such a library |
US5614940A (en) * | 1994-10-21 | 1997-03-25 | Intel Corporation | Method and apparatus for providing broadcast information with indexing |
US6029195A (en) * | 1994-11-29 | 2000-02-22 | Herz; Frederick S. M. | System for customized electronic identification of desirable objects |
US5729656A (en) | 1994-11-30 | 1998-03-17 | International Business Machines Corporation | Reduction of search space in speech recognition using phone boundaries and phone ranking |
US5638487A (en) * | 1994-12-30 | 1997-06-10 | Purespeech, Inc. | Automatic speech recognition |
US5715367A (en) * | 1995-01-23 | 1998-02-03 | Dragon Systems, Inc. | Apparatuses and methods for developing and using models for speech recognition |
US5684924A (en) | 1995-05-19 | 1997-11-04 | Kurzweil Applied Intelligence, Inc. | User adaptable speech recognition system |
US5559875A (en) * | 1995-07-31 | 1996-09-24 | Latitude Communications | Method and apparatus for recording and retrieval of audio conferences |
US6151598A (en) * | 1995-08-14 | 2000-11-21 | Shaw; Venson M. | Digital dictionary with a communication system for the creating, updating, editing, storing, maintaining, referencing, and managing the digital dictionary |
US5963940A (en) * | 1995-08-16 | 1999-10-05 | Syracuse University | Natural language information retrieval system and method |
US6026388A (en) * | 1995-08-16 | 2000-02-15 | Textwise, Llc | User interface and other enhancements for natural language information retrieval system and method |
US6006221A (en) | 1995-08-16 | 1999-12-21 | Syracuse University | Multilingual document retrieval system and method using semantic vector matching |
US20020002562A1 (en) | 1995-11-03 | 2002-01-03 | Thomas P. Moran | Computer controlled display system using a graphical replay device to control playback of temporal data representing collaborative activities |
US5960447A (en) * | 1995-11-13 | 1999-09-28 | Holt; Douglas | Word tagging and editing system for speech recognition |
JPH09269931A (en) * | 1996-01-30 | 1997-10-14 | Canon Inc | Cooperative work environment constructing system, its method and medium |
US6067517A (en) * | 1996-02-02 | 2000-05-23 | International Business Machines Corporation | Transcription of speech data with segments from acoustically dissimilar environments |
DE69712277T2 (en) * | 1996-02-27 | 2002-12-19 | Koninkl Philips Electronics Nv | METHOD AND DEVICE FOR AUTOMATIC VOICE SEGMENTATION IN PHONEMIC UNITS |
US5862259A (en) | 1996-03-27 | 1999-01-19 | Caere Corporation | Pattern recognition employing arbitrary segmentation and compound probabilistic evaluation |
US6024571A (en) * | 1996-04-25 | 2000-02-15 | Renegar; Janet Elaine | Foreign language communication system/device and learning aid |
US5778187A (en) * | 1996-05-09 | 1998-07-07 | Netcast Communications Corp. | Multicasting method and apparatus |
US5996022A (en) * | 1996-06-03 | 1999-11-30 | Webtv Networks, Inc. | Transcoding data in a proxy computer prior to transmitting the audio data to a client |
US5806032A (en) * | 1996-06-14 | 1998-09-08 | Lucent Technologies Inc. | Compilation of weighted finite-state transducers from decision trees |
US6169789B1 (en) * | 1996-12-16 | 2001-01-02 | Sanjay K. Rao | Intelligent keyboard system |
US5897614A (en) * | 1996-12-20 | 1999-04-27 | International Business Machines Corporation | Method and apparatus for sibilant classification in a speech recognition system |
US6732183B1 (en) * | 1996-12-31 | 2004-05-04 | Broadware Technologies, Inc. | Video and audio streaming for multiple users |
US6185531B1 (en) * | 1997-01-09 | 2001-02-06 | Gte Internetworking Incorporated | Topic indexing method |
US6088669A (en) | 1997-01-28 | 2000-07-11 | International Business Machines, Corporation | Speech recognition with attempted speaker recognition for speaker model prefetching or alternative speech modeling |
JP2991287B2 (en) * | 1997-01-28 | 1999-12-20 | 日本電気株式会社 | Suppression standard pattern selection type speaker recognition device |
US6029124A (en) * | 1997-02-21 | 2000-02-22 | Dragon Systems, Inc. | Sequential, nonparametric speech recognition and speaker identification |
US6463444B1 (en) * | 1997-08-14 | 2002-10-08 | Virage, Inc. | Video cataloger system with extensibility |
US6567980B1 (en) * | 1997-08-14 | 2003-05-20 | Virage, Inc. | Video cataloger system with hyperlinked output |
US6360234B2 (en) * | 1997-08-14 | 2002-03-19 | Virage, Inc. | Video cataloger system with synchronized encoders |
US6052657A (en) * | 1997-09-09 | 2000-04-18 | Dragon Systems, Inc. | Text segmentation and identification of topic using language models |
US6317716B1 (en) | 1997-09-19 | 2001-11-13 | Massachusetts Institute Of Technology | Automatic cueing of speech |
JP2001511991A (en) | 1997-10-01 | 2001-08-14 | エイ・ティ・アンド・ティ・コーポレーション | Method and apparatus for storing and retrieving label interval data for multimedia records |
US6961954B1 (en) * | 1997-10-27 | 2005-11-01 | The Mitre Corporation | Automated segmentation, information extraction, summarization, and presentation of broadcast news |
US6064963A (en) * | 1997-12-17 | 2000-05-16 | Opus Telecom, L.L.C. | Automatic key word or phrase speech recognition for the corrections industry |
JP4183311B2 (en) * | 1997-12-22 | 2008-11-19 | 株式会社リコー | Document annotation method, annotation device, and recording medium |
US5970473A (en) * | 1997-12-31 | 1999-10-19 | At&T Corp. | Video communication device providing in-home catalog services |
SE511584C2 (en) * | 1998-01-15 | 1999-10-25 | Ericsson Telefon Ab L M | information Routing |
US6327343B1 (en) | 1998-01-16 | 2001-12-04 | International Business Machines Corporation | System and methods for automatic call and data transfer processing |
JP3181548B2 (en) * | 1998-02-03 | 2001-07-03 | 富士通株式会社 | Information retrieval apparatus and information retrieval method |
US6073096A (en) * | 1998-02-04 | 2000-06-06 | International Business Machines Corporation | Speaker adaptation system and method based on class-specific pre-clustering training speakers |
US7257528B1 (en) * | 1998-02-13 | 2007-08-14 | Zi Corporation Of Canada, Inc. | Method and apparatus for Chinese character text input |
US6381640B1 (en) * | 1998-09-11 | 2002-04-30 | Genesys Telecommunications Laboratories, Inc. | Method and apparatus for automated personalization and presentation of workload assignments to agents within a multimedia communication center |
US6112172A (en) * | 1998-03-31 | 2000-08-29 | Dragon Systems, Inc. | Interactive searching |
CN1159662C (en) * | 1998-05-13 | 2004-07-28 | 国际商业机器公司 | Automatic punctuating for continuous speech recognition |
US6076053A (en) * | 1998-05-21 | 2000-06-13 | Lucent Technologies Inc. | Methods and apparatus for discriminative training and adaptation of pronunciation networks |
US6243680B1 (en) * | 1998-06-15 | 2001-06-05 | Nortel Networks Limited | Method and apparatus for obtaining a transcription of phrases through text and spoken utterances |
US6067514A (en) * | 1998-06-23 | 2000-05-23 | International Business Machines Corporation | Method for automatically punctuating a speech utterance in a continuous speech recognition system |
US6246983B1 (en) * | 1998-08-05 | 2001-06-12 | Matsushita Electric Corporation Of America | Text-to-speech e-mail reader with multi-modal reply processor |
US6373985B1 (en) * | 1998-08-12 | 2002-04-16 | Lucent Technologies, Inc. | E-mail signature block analysis |
US6360237B1 (en) * | 1998-10-05 | 2002-03-19 | Lernout & Hauspie Speech Products N.V. | Method and system for performing text edits during audio recording playback |
US6161087A (en) * | 1998-10-05 | 2000-12-12 | Lernout & Hauspie Speech Products N.V. | Speech-recognition-assisted selective suppression of silent and filled speech pauses during playback of an audio recording |
US6347295B1 (en) * | 1998-10-26 | 2002-02-12 | Compaq Computer Corporation | Computer method and apparatus for grapheme-to-phoneme rule-set-generation |
US6332139B1 (en) * | 1998-11-09 | 2001-12-18 | Mega Chips Corporation | Information communication system |
JP3252282B2 (en) * | 1998-12-17 | 2002-02-04 | 松下電器産業株式会社 | Method and apparatus for searching scene |
US6654735B1 (en) * | 1999-01-08 | 2003-11-25 | International Business Machines Corporation | Outbound information analysis for generating user interest profiles and improving user productivity |
US6253179B1 (en) * | 1999-01-29 | 2001-06-26 | International Business Machines Corporation | Method and apparatus for multi-environment speaker verification |
DE19912405A1 (en) * | 1999-03-19 | 2000-09-21 | Philips Corp Intellectual Pty | Determination of a regression class tree structure for speech recognizers |
CN1148965C (en) | 1999-03-30 | 2004-05-05 | 提维股份有限公司 | Data storage management and scheduling system |
US6345252B1 (en) * | 1999-04-09 | 2002-02-05 | International Business Machines Corporation | Methods and apparatus for retrieving audio information using content and speaker information |
US6434520B1 (en) * | 1999-04-16 | 2002-08-13 | International Business Machines Corporation | System and method for indexing and querying audio archives |
US6711585B1 (en) * | 1999-06-15 | 2004-03-23 | Kanisa Inc. | System and method for implementing a knowledge management system |
US6219640B1 (en) * | 1999-08-06 | 2001-04-17 | International Business Machines Corporation | Methods and apparatus for audio-visual speaker recognition and utterance verification |
IES990800A2 (en) | 1999-08-20 | 2000-09-06 | Digitake Software Systems Ltd | An audio processing system |
JP3232289B2 (en) * | 1999-08-30 | 2001-11-26 | インターナショナル・ビジネス・マシーンズ・コーポレーション | Symbol insertion device and method |
US6480826B2 (en) * | 1999-08-31 | 2002-11-12 | Accenture Llp | System and method for a telephonic emotion detection that provides operator feedback |
US6711541B1 (en) * | 1999-09-07 | 2004-03-23 | Matsushita Electric Industrial Co., Ltd. | Technique for developing discriminative sound units for speech recognition and allophone modeling |
US6624826B1 (en) * | 1999-09-28 | 2003-09-23 | Ricoh Co., Ltd. | Method and apparatus for generating visual representations for audio documents |
US6571208B1 (en) * | 1999-11-29 | 2003-05-27 | Matsushita Electric Industrial Co., Ltd. | Context-dependent acoustic models for medium and large vocabulary speech recognition with eigenvoice training |
JP2003518266A (en) * | 1999-12-20 | 2003-06-03 | コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ | Speech reproduction for text editing of speech recognition system |
WO2001063597A1 (en) | 2000-02-25 | 2001-08-30 | Koninklijke Philips Electronics N.V. | Speech recognition device with reference transformation means |
US7197694B2 (en) * | 2000-03-21 | 2007-03-27 | Oki Electric Industry Co., Ltd. | Image display system, image registration terminal device and image reading terminal device used in the image display system |
US7120575B2 (en) * | 2000-04-08 | 2006-10-10 | International Business Machines Corporation | Method and system for the automatic segmentation of an audio stream into semantic or syntactic units |
CN1193605C (en) * | 2000-04-21 | 2005-03-16 | 松下电器产业株式会社 | Data reproduction apparatus |
US6505153B1 (en) * | 2000-05-22 | 2003-01-07 | Compaq Information Technologies Group, L.P. | Efficient method for producing off-line closed captions |
US6748356B1 (en) * | 2000-06-07 | 2004-06-08 | International Business Machines Corporation | Methods and apparatus for identifying unknown speakers using a hierarchical tree structure |
JP2002008389A (en) * | 2000-06-20 | 2002-01-11 | Mitsubishi Electric Corp | Semiconductor memory |
US7047192B2 (en) * | 2000-06-28 | 2006-05-16 | Poirier Darrell A | Simultaneous multi-user real-time speech recognition system |
EP1176493A3 (en) | 2000-07-28 | 2002-07-10 | Jan Pathuel | Method and system of securing data and systems |
WO2002010981A2 (en) | 2000-07-28 | 2002-02-07 | Easyask, Inc. | Distributed search system and method |
WO2002019147A1 (en) * | 2000-08-28 | 2002-03-07 | Emotion, Inc. | Method and apparatus for digital media management, retrieval, and collaboration |
US6604110B1 (en) * | 2000-08-31 | 2003-08-05 | Ascential Software, Inc. | Automated software code generation from a metadata-based repository |
US6647383B1 (en) * | 2000-09-01 | 2003-11-11 | Lucent Technologies Inc. | System and method for providing interactive dialogue and iterative search functions to find information |
AU2000276394A1 (en) | 2000-09-30 | 2002-04-15 | Intel Corporation | Method and system for generating and searching an optimal maximum likelihood decision tree for hidden markov model (hmm) based speech recognition |
WO2002029614A1 (en) | 2000-09-30 | 2002-04-11 | Intel Corporation | Method and system to scale down a decision tree-based hidden markov model (hmm) for speech recognition |
US6934756B2 (en) * | 2000-11-01 | 2005-08-23 | International Business Machines Corporation | Conversational networking via transport, coding and control conversational protocols |
US20050060162A1 (en) * | 2000-11-10 | 2005-03-17 | Farhad Mohit | Systems and methods for automatic identification and hyperlinking of words or other data items and for information retrieval using hyperlinked words or data items |
US7221663B2 (en) | 2001-12-31 | 2007-05-22 | Polycom, Inc. | Method and apparatus for wideband conferencing |
SG98440A1 (en) * | 2001-01-16 | 2003-09-19 | Reuters Ltd | Method and apparatus for a financial database structure |
US6725198B2 (en) | 2001-01-25 | 2004-04-20 | Harcourt Assessment, Inc. | Speech analysis system and method |
US20020133477A1 (en) * | 2001-03-05 | 2002-09-19 | Glenn Abel | Method for profile-based notice and broadcast of multimedia content |
ATE335195T1 (en) * | 2001-05-10 | 2006-08-15 | Koninkl Philips Electronics Nv | BACKGROUND LEARNING OF SPEAKER VOICES |
US6973428B2 (en) | 2001-05-24 | 2005-12-06 | International Business Machines Corporation | System and method for searching, analyzing and displaying text transcripts of speech after imperfect speech recognition |
US6778979B2 (en) * | 2001-08-13 | 2004-08-17 | Xerox Corporation | System for automatically generating queries |
US6748350B2 (en) * | 2001-09-27 | 2004-06-08 | Intel Corporation | Method to compensate for stress between heat spreader and thermal interface material |
US6708148B2 (en) * | 2001-10-12 | 2004-03-16 | Koninklijke Philips Electronics N.V. | Correction device to mark parts of a recognized text |
US20030093580A1 (en) * | 2001-11-09 | 2003-05-15 | Koninklijke Philips Electronics N.V. | Method and system for information alerts |
US7165024B2 (en) * | 2002-02-22 | 2007-01-16 | Nec Laboratories America, Inc. | Inferring hierarchical descriptions of a set of documents |
US7668816B2 (en) * | 2002-06-11 | 2010-02-23 | Microsoft Corporation | Dynamically updated quick searches and strategies |
US7131117B2 (en) | 2002-09-04 | 2006-10-31 | Sbc Properties, L.P. | Method and system for automating the analysis of word frequencies |
US6999918B2 (en) * | 2002-09-20 | 2006-02-14 | Motorola, Inc. | Method and apparatus to facilitate correlating symbols to sounds |
US7580838B2 (en) | 2002-11-22 | 2009-08-25 | Scansoft, Inc. | Automatic insertion of non-verbalized punctuation |
-
2003
- 2003-10-16 US US10/685,479 patent/US20040163034A1/en not_active Abandoned
- 2003-10-16 US US10/685,478 patent/US20040083104A1/en not_active Abandoned
- 2003-10-16 US US10/685,445 patent/US20040138894A1/en not_active Abandoned
- 2003-10-16 US US10/685,410 patent/US7389229B2/en not_active Expired - Fee Related
- 2003-10-16 US US10/685,585 patent/US7424427B2/en active Active
- 2003-10-16 US US10/685,586 patent/US20040204939A1/en not_active Abandoned
- 2003-10-16 US US10/685,403 patent/US20040083090A1/en not_active Abandoned
- 2003-10-16 US US10/685,565 patent/US7292977B2/en active Active - Reinstated
- 2003-10-16 US US10/685,566 patent/US20040176946A1/en not_active Abandoned
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6931376B2 (en) * | 2000-07-20 | 2005-08-16 | Microsoft Corporation | Speech-related event notification system |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120109638A1 (en) * | 2010-10-27 | 2012-05-03 | Hon Hai Precision Industry Co., Ltd. | Electronic device and method for extracting component names using the same |
Also Published As
Publication number | Publication date |
---|---|
US20040083104A1 (en) | 2004-04-29 |
US7424427B2 (en) | 2008-09-09 |
US20040176946A1 (en) | 2004-09-09 |
US7389229B2 (en) | 2008-06-17 |
US20050038649A1 (en) | 2005-02-17 |
US20040163034A1 (en) | 2004-08-19 |
US20040204939A1 (en) | 2004-10-14 |
US20040230432A1 (en) | 2004-11-18 |
US20040172250A1 (en) | 2004-09-02 |
US20040138894A1 (en) | 2004-07-15 |
US7292977B2 (en) | 2007-11-06 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20040083090A1 (en) | Manager for integrating language technology components | |
US7257817B2 (en) | Virtual network with adaptive dispatcher | |
US7840633B2 (en) | Communicating messages between components in a client/server environment using an object broker | |
US20090046726A1 (en) | Virtual network with adaptive dispatcher | |
US8683273B2 (en) | Method and system for notifying error information in a network | |
US20080109828A1 (en) | Application component communication apparatus of sca-based system and method thereof | |
CN102223258B (en) | Method and device for preventing BFD (bidirectional forwarding detection) conversation interruption | |
WO2006124178A2 (en) | Proxy for application server | |
US20020031214A1 (en) | Interface for interfacing client programs with network devices in a telecommunications network | |
US7418508B2 (en) | System and method to facilitate XML enabled IMS transactions between a remote client and an IMS application program | |
JP2004062535A (en) | Method of dealing with failure for multiprocessor system, multiprocessor system and node | |
CN112799786A (en) | Exit method, device, equipment and storage medium of micro-service instance | |
US7739389B2 (en) | Providing web services from a service environment with a gateway | |
CN110519079B (en) | Data forwarding method and device, network board, network equipment and storage medium | |
US11165750B1 (en) | Flexible services-based pipeline for firewall filter processing | |
CN102819455B (en) | A kind of method process being managed in application layer and management system | |
US20090085916A1 (en) | Method and Apparatus for Performing Non Service Affecting Software Upgrades in Place | |
WO2022121492A1 (en) | File transmission method and apparatus, computer device, and storage medium | |
CN115484232A (en) | DHCP server deployment method, device, equipment and storage medium | |
Cisco | Release Notes for the Cisco SIP Proxy Server Version 1.3 on Linux | |
Cisco | Release Notes for the Cisco SIP Proxy Server Version 1.3 on Solaris | |
US8141065B2 (en) | Method and apparatus for performing non service affecting software upgrades in place | |
CN108683540B (en) | Cross-platform lightweight implementation method and system for network management protocol channel | |
Cisco | Release Notes for Cisco MGX 8260 Media Gateway, Version 1.2.5 | |
WO2021035791A1 (en) | Method for controlling other systems on the basis of single-point execution contract |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: BBNT SOLUTIONS LLC, TEXAS Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KIECZA, DANIEL;KUBALA, FRANCIS;ALLEN, PETER G.;REEL/FRAME:014619/0728;SIGNING DATES FROM 20031001 TO 20031003 |
|
AS | Assignment |
Owner name: FLEET NATIONAL BANK, AS AGENT, MASSACHUSETTS Free format text: PATENT & TRADEMARK SECURITY AGREEMENT;ASSIGNOR:BBNT SOLUTIONS LLC;REEL/FRAME:014624/0196 Effective date: 20040326 Owner name: FLEET NATIONAL BANK, AS AGENT,MASSACHUSETTS Free format text: PATENT & TRADEMARK SECURITY AGREEMENT;ASSIGNOR:BBNT SOLUTIONS LLC;REEL/FRAME:014624/0196 Effective date: 20040326 |
|
AS | Assignment |
Owner name: BBNT SOLUTIONS LLC, MASSACHUSETTS Free format text: CORRECTED RECORDATION COVER SHEET PREVIOUSLY RECORDED ON REEL 014619 FRAME 0728;ASSIGNORS:KIECZA, DANIEL;KUBALA, FRANCIS G.;ALLEN, PETER G.;REEL/FRAME:015816/0409;SIGNING DATES FROM 20031001 TO 20031003 |
|
AS | Assignment |
Owner name: BBN TECHNOLOGIES CORP.,MASSACHUSETTS Free format text: MERGER;ASSIGNOR:BBNT SOLUTIONS LLC;REEL/FRAME:017274/0318 Effective date: 20060103 Owner name: BBN TECHNOLOGIES CORP., MASSACHUSETTS Free format text: MERGER;ASSIGNOR:BBNT SOLUTIONS LLC;REEL/FRAME:017274/0318 Effective date: 20060103 |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |
|
AS | Assignment |
Owner name: BBN TECHNOLOGIES CORP. (AS SUCCESSOR BY MERGER TO Free format text: RELEASE OF SECURITY INTEREST;ASSIGNOR:BANK OF AMERICA, N.A. (SUCCESSOR BY MERGER TO FLEET NATIONAL BANK);REEL/FRAME:023427/0436 Effective date: 20091026 |