Abstract: A computer-based system includes a computer-processable definition of a region in a data set. The system identifies a region of the data set based on the definition of the region. The system provides output to a user representing a question and the identified region of the data set. The system may also automatically generate an answer to the question based on the question and the data set, and provide output to the user representing the answer. The system may generate the answer based on a subset of the data set, and provide output to the user representing the subset of the data set. The user may provide feedback on the first answer to the system, which the system may use to improve subsequent answers to the same and other questions, and to disable the system's automatic question-answering function in response to disagreement between the user and the system.

Abstract: A system is provided for training an acoustic model for use in speech recognition. In particular, such a system may be used to perform training based on a spoken audio stream and a non-literal transcript of the spoken audio stream. Such a system may identify text in the non-literal transcript which represents concepts having multiple spoken forms. The system may attempt to identify the actual spoken form in the audio stream which produced the corresponding text in the non-literal transcript, and thereby produce a revised transcript which more accurately represents the spoken audio stream. The revised, and more accurate, transcript may be used to train the acoustic model, thereby producing a better acoustic model than that which would be produced using conventional techniques, which perform training based directly on the original non-literal transcript.

Abstract: An automatic speech recognizer is used to produce a structured document representing the contents of human speech. A best practice is applied to the structured document to produce a conclusion, such as a conclusion that required information is missing from the structured document. Content is inserted into the structured document based on the conclusion, thereby producing a modified document. The inserted content may be obtained by prompting a human user for the content and receiving input representing the content from the human user.

Abstract: An automatic speech recognition system includes an audio capture component, a speech recognition processing component, and a result processing component which are distributed among two or more logical devices and/or two or more physical devices. In particular, the audio capture component may be located on a different logical device and/or physical device from the result processing component. For example, the audio capture component may be on a computer connected to a microphone into which a user speaks, while the result processing component may be on a terminal server which receives speech recognition results from a speech recognition processing server.

Abstract: A system is provided for training an acoustic model for use in speech recognition. In particular, such a system may be used to perform training based on a spoken audio stream and a non-literal transcript of the spoken audio stream. Such a system may identify text in the non-literal transcript which represents concepts having multiple spoken forms. The system may attempt to identify the actual spoken form in the audio stream which produced the corresponding text in the non-literal transcript, and thereby produce a revised transcript which more accurately represents the spoken audio stream. The revised, and more accurate, transcript may be used to train the acoustic model, thereby producing a better acoustic model than that which would be produced using conventional techniques, which perform training based directly on the original non-literal transcript.

Abstract: An automatic speech recognizer is used to produce a structured document representing the contents of human speech. A best practice is applied to the structured document to produce a conclusion, such as a conclusion that required information is missing from the structured document. Content is inserted into the structured document based on the conclusion, thereby producing a modified document. The inserted content may be obtained by prompting a human user for the content and receiving input representing the content from the human user.

Abstract: Techniques are disclosed for facilitating the process of proofreading draft transcripts of spoken audio streams. In general, proofreading of a draft transcript is facilitated by playing back the corresponding spoken audio stream with an emphasis on those regions in the audio stream that are highly relevant or likely to have been transcribed incorrectly. Regions may be emphasized by, for example, playing them back more slowly than regions that are of low relevance and likely to have been transcribed correctly. Emphasizing those regions of the audio stream that are most important to transcribe correctly and those regions that are most likely to have been transcribed incorrectly increases the likelihood that the proofreader will accurately correct any errors in those regions, thereby improving the overall accuracy of the transcript.

Abstract: A computer-based system includes a computer-processable definition of a region in a data set. The system identifies a region of the data set based on the definition of the region. The system provides output to a user representing a question and the identified region of the data set. The system may also automatically generate an answer to the question based on the question and the data set, and provide output to the user representing the answer. The system may generate the answer based on a subset of the data set, and provide output to the user representing the subset of the data set. The user may provide feedback on the first answer to the system, which the system may use to improve subsequent answers to the same and other questions, and to disable the system's automatic question-answering function in response to disagreement between the user and the system.

Abstract: An automatic speech recognition system includes an audio capture component, a speech recognition processing component, and a result processing component which are distributed among two or more logical devices and/or two or more physical devices. In particular, the audio capture component may be located on a different logical device and/or physical device from the result processing component. For example, the audio capture component may be on a computer connected to a microphone into which a user speaks, while the result processing component may be on a terminal server which receives speech recognition results from a speech recognition processing server.

Abstract: Techniques are disclosed for facilitating the process of proofreading draft transcripts of spoken audio streams. In general, proofreading of a draft transcript is facilitated by playing back the corresponding spoken audio stream with an emphasis on those regions in the audio stream that are highly relevant or likely to have been transcribed incorrectly. Regions may be emphasized by, for example, playing them back more slowly than regions that are of low relevance and likely to have been transcribed correctly. Emphasizing those regions of the audio stream that are most important to transcribe correctly and those regions that are most likely to have been transcribed incorrectly increases the likelihood that the proofreader will accurately correct any errors in those regions, thereby improving the overall accuracy of the transcript.

Abstract: An automatic speech recognition system includes an audio capture component, a speech recognition processing component, and a result processing component which are distributed among two or more logical devices and/or two or more physical devices. In particular, the audio capture component may be located on a different logical device and/or physical device from the result processing component. For example, the audio capture component may be on a computer connected to a microphone into which a user speaks, while the result processing component may be on a terminal server which receives speech recognition results from a speech recognition processing server.

Abstract: A computer-based system includes a computer-processable definition of a region in a data set. The system identifies a region of the data set based on the definition of the region. The system provides output to a user representing a question and the identified region of the data set. The system may also automatically generate an answer to the question based on the question and the data set, and provide output to the user representing the answer. The system may generate the answer based on a subset of the data set, and provide output to the user representing the subset of the data set. The user may provide feedback on the first answer to the system, which the system may use to improve subsequent answers to the same and other questions, and to disable the system's automatic question-answering function in response to disagreement between the user and the system.

Abstract: An automatic speech recognition system includes an audio capture component, a speech recognition processing component, and a result processing component which are distributed among two or more logical devices and/or two or more physical devices. In particular, the audio capture component may be located on a different logical device and/or physical device from the result processing component. For example, the audio capture component may be on a computer connected to a microphone into which a user speaks, while the result processing component may be on a terminal server which receives speech recognition results from a speech recognition processing server.

Abstract: A speech recognition client sends a speech stream and control stream in parallel to a server-side speech recognizer over a network. The network may be an unreliable, low-latency network. The server-side speech recognizer recognizes the speech stream continuously. The speech recognition client receives recognition results from the server-side recognizer in response to requests from the client. The client may remotely reconfigure the state of the server-side recognizer during recognition.

Abstract: A system includes a document corpus containing structured documents, which contain both text and annotations of the text. The system also includes a search engine which is adapted to perform structured searches of the structured documents. As new types of annotations are added to the system, the search engine is updated automatically to become capable of performing structured searches for the new types of annotations. For example, if a new natural language processing (NLP) component, adapted to generate annotations of a new type, is added to the system, then the system automatically updates a query language to include a definition of the new type of annotation. The search engine may then immediately be capable of processing structured queries which refer to the new type of annotation.

Abstract: Non-verbalized tokens, such as punctuation, are automatically predicted and inserted into a transcription of speech in which the tokens were not explicitly verbalized. Token prediction may be integrated with speech decoding, rather than performed as a post-process to speech decoding.

Abstract: A system includes a document corpus containing structured documents, which contain both text and annotations of the text. The system also includes a search engine which is adapted to perform structured searches of the structured documents. As new types of annotations are added to the system, the search engine is updated automatically to become capable of performing structured searches for the new types of annotations. For example, if a new natural language processing (NLP) component, adapted to generate annotations of a new type, is added to the system, then the system automatically updates a query language to include a definition of the new type of annotation. The search engine may then immediately be capable of processing structured queries which refer to the new type of annotation.

Abstract: Non-verbalized tokens, such as punctuation, are automatically predicted and inserted into a transcription of speech in which the tokens were not explicitly verbalized. Token prediction may be integrated with speech decoding, rather than performed as a post-process to speech decoding.

Abstract: An automatic speech recognizer is used to produce a structured document representing the contents of human speech. A best practice is applied to the structured document to produce a conclusion, such as a conclusion that required information is missing from the structured document. Content is inserted into the structured document based on the conclusion, thereby producing a modified document. The inserted content may be obtained by prompting a human user for the content and receiving input representing the content from the human user.

Abstract: Facts are extracted from speech and recorded in a document using codings. Each coding represents an extracted fact and includes a code and a datum. The code may represent a type of the extracted fact and the datum may represent a value of the extracted fact. The datum in a coding is rendered based on a specified feature of the coding. For example, the datum may be rendered as boldface text to indicate that the coding has been designated as an “allergy.” In this way, the specified feature of the coding (e.g., “allergy”-ness) is used to modify the manner in which the datum is rendered. A user inspects the rendering and provides, based on the rendering, an indication of whether the coding was accurately designated as having the specified feature. A record of the user's indication may be stored, such as within the coding itself.