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 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 using discriminative training techniques, 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: A computer system uses a search engine to search a dataset using an initial query provided by a user and thereby to produce initial search results. The system enables the user to select portions of the initial search results. The system identifies metadata associated with the selected portions, and displays information representing that metadata in a form that is easily understandable by a person not trained in the annotation system in which the search results are encoded. The user may instruct the system to add one or more of the displayed metadata elements to the initial query, in response to which the system may add the specified metadata elements to the initial query to produce a modified query. The system may search the dataset using the modified query and thereby produce modified search results. The process may be repeated as desired by the user to further refine the search results.

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: A computer-assisted method of abstracting and coding data includes receiving one or more documents is disclosed. The methods and systems extract information from a record based on extraction rules that correspond to an identified record type, determine codes corresponding to the information extracted from the record, present the correspondence between the extracted information and the codes, receive from the user-input device a validation of the correspondence between the extracted information and one of the codes, and output a report including the validated information and the validated code.

Abstract: Methods and systems are disclosed for tracking quality measures in abstracted documents. Embodiments include, determining, based on the abstracted content, a quality measure category, obtaining a quality measure definition corresponding to a quality measure included in the determined quality measure category, determining, based on keywords corresponding to the criterion, whether a portion of the abstracted content satisfies a criterion, recording, in association with the criterion, a reference to the portion of the abstracted content that satisfies the criterion; and selectively generating, a report including the query corresponding to the criterion, a query response, and the portion of the abstracted content satisfying the criterion.

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: Methods and systems are disclosed for tracking quality measures in abstracted documents. Embodiments include, determining, based on the abstracted content, a quality measure category, obtaining a quality measure definition corresponding to a quality measure included in the determined quality measure category, determining, based on keywords corresponding to the criterion, whether a portion of the abstracted content satisfies a criterion, recording, in association with the criterion, a reference to the portion of the abstracted content that satisfies the criterion; and selectively generating, a report including the query corresponding to the criterion, a query response, and the portion of the abstracted content satisfying the criterion.

Abstract: A computer system generates an initial set of billing codes based on one or more documents (e.g., clinical notes) representing a patient encounter, such as clinical notes created by a physician. The system expands the initial set of billing codes based on a billing code standard to create an expanded set of billing codes for consideration by the physician. The system provides output representing the expanded billing code set to the physician. The physician selects one or more billing codes from the expanded billing code set for inclusion in a final billing code set for use in a bill for the services provided in the patient encounter.

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 using discriminative training techniques, 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: A graphical user interface, referred to herein as a virtual whiteboard, that provides both: (1) an automatically prioritized display of information related to a particular patient that is tailored to the current user of the system, and (2) a “scratch pad” area in which multiple users of the system may input free-form text and other data for sharing with other users of the system. When each user of the system accesses the virtual whiteboard, the system: (1) automatically prioritizes the patient information based on characteristics of the user and displays the automatically prioritized patient information to that user, and (2) displays the contents of the scratch pad to the user. As a result, the whiteboard displays both information that is tailored to the current user and information that is common to all users (i.e., not tailored to any particular user).

Abstract: A computer system generates an initial set of billing codes based on one or more documents (e.g., clinical notes) representing a patient encounter, such as clinical notes created by a physician. The system expands the initial set of billing codes based on a billing code standard to create an expanded set of billing codes for consideration by the physician. The system provides output representing the expanded billing code set to the physician. The physician selects one or more billing codes from the expanded billing code set for inclusion in a final billing code set for use in a bill for the services provided in the patient encounter.

Abstract: A graphical user interface, referred to herein as a virtual whiteboard, that provides both: (1) an automatically prioritized display of information related to a particular patient that is tailored to the current user of the system, and (2) a “scratch pad” area in which multiple users of the system may input free-form text and other data for sharing with other users of the system. When each user of the system accesses the virtual whiteboard, the system: (1) automatically prioritizes the patient information based on characteristics of the user and displays the automatically prioritized patient information to that user, and (2) displays the contents of the scratch pad to the user. As a result, the whiteboard displays both information that is tailored to the current user and information that is common to all users (i.e., not tailored to any particular user).

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.