Burlington, MA, United States

Nuance Communications

www.nuance.com
Burlington, MA, United States

Nuance Communications is an American multinational computer software technology corporation, headquartered in Burlington, Massachusetts, United States,a suburb of Boston, that provides speech and imaging applications. Current business products focus on server & embedded speech recognition, telephone call steering systems, automated telephone directory services, medical transcription software & systems, optical character recognition software, and desktop imaging software. The company also maintains a small division which does software and system development for military and government agencies. In October 2011, unconfirmed research suggested that its servers power Apple's iPhone 4S Siri voice recognition application.As of 2008, the company is a result of organic growth, mergers, and acquisitions. ScanSoft and Nuance merged in October 2005; before the merger, the two companies competed in the commercial large scale speech application business. The officially termed "merger" was a de facto acquisition of Nuance by ScanSoft, though the combined company changed its name to Nuance following the transaction. Before 1999, ScanSoft was known as Visioneer, a hardware and software scanner company. In 1999, Visioneer bought ScanSoft – a Xerox spin-off – and adopted ScanSoft as the company name. The original ScanSoft had its roots in Kurzweil Computer Products, a software company that developed the first omni-font character recognition system. Wikipedia.

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Patent
Nuance Communications | Date: 2017-03-08

Techniques are provided whereby a clarification request may be generated with a clinical documentation improvement (CDI) system for resolution by a clinician, and notification of the clarification request may be transmitted to a medical coding system. At a medical coding system, notification may be received of a clarification request generated at a CDI system for resolution by a clinician. In some embodiments, the medical coding system may be a computer-assisted coding (CAC) system.


Technology is described for developing a language model for a language recognition system from scratch based on aggregating and analyzing text input from multiple users of the language. The technology allows a user to select a language, and if no existing language model is available for the selected language, provides a new language model for the selected language, monitors and collects information about the use of words in the selected language, combines information collected from multiple users of the selected language, and updates the users language model based on the combined information from multiple users of the selected language.


Aspects described herein provide various approaches to annotating text samples in order to construct natural language grammars. A text sample may be selected for annotation. A set of annotation candidates may be generated based on the text sample. A classifier may be used to score the set of annotation candidates in order to obtain a set of annotation scores. One of the annotation candidates may be selected as a suggested annotation for the text sample based on the set of annotation scores. A grammar rule may be derived based on the suggested annotation, and a grammar may be configured to include the annotation-derived grammar rule.


Patent
Nuance Communications | Date: 2017-03-08

Techniques for training a natural language understanding (NLU) engine may include generating a first annotation of free-form text documenting a healthcare patient encounter and a link between the first annotation and a corresponding portion of the text, using the NLU engine. A second annotation of the text and a link between the second annotation and a corresponding portion of the text may be received from a human user. The first annotation and its corresponding link may be merged with the second annotation and its corresponding link. Training data may be provided to the engine in the form of the text and the merged annotations and links.


Patent
Nuance Communications | Date: 2017-02-13

In accordance with aspects of the disclosure, a computing device may identify a prompt associated with an automated dialog application. An application expectation of the automated dialog application may be identified. The application expectation may comprise a structured natural language representation for a natural language response to the prompt. The computing device may receive natural language input responsive to the prompt, populate one or more data fields of the structured natural language representation with at least a portion of the natural language input, and may respond to the application expectation using the one or more data fields of the structured natural language representation.


Patent
Nuance Communications | Date: 2017-01-10

An automotive text display arrangement is described which includes a driver text display positioned directly in front of an automobile driver and displaying a limited amount of text to the driver without impairing forward visual attention of the driver. The arrangement may include a boundary insertion mode wherein when the active text position is an active text boundary, new text is inserted between the text items separated by the active text boundary, and when the active text position is an active text item, new text replaces the active text item. In addition or alternatively, there may be a multifunctional text control knob offering multiple different user movements, each performing an associated text processing function.


Patent
Nuance Communications | Date: 2017-02-02

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for presenting a machine translation and alternative translations to a user, where a selection of any particular alternative translation results in the re-ranking of the remaining alternatives. The system then presents these re-ranked alternatives to the user, who can continue proofing the machine translation using the re-ranked alternatives or by typing an improved translation. This process continues until the user indicates that the current portion of the translation is complete, at which point the system moves to the next portion.


Patent
Nuance Communications | Date: 2017-05-10

According to some aspects, a method of searching for content in response to a user voice query is provided. The method may comprise receiving the user voice query, performing speech recognition to generate N best speech recognition results comprising a first speech recognition result, performing a supervised search of at least one content repository to identify one or more supervised search results using one or more classifiers that classify the first speech recognition result into at least one class that identifies previously classified content in the at least one content repository, performing an unsupervised search of the at least one content repository to identify one or more unsupervised search results, wherein performing the unsupervised search comprises performing a word search of the at least one content repository, and generating combined results from among the one or more supervised search results and the one or more unsupervised search results.


Patent
Nuance Communications | Date: 2017-01-03

Techniques for documenting a clinical procedure involve transcribing audio data comprising audio of one or more clinical personnel speaking while performing the clinical procedure. Examples of applicable clinical procedures include sterile procedures such as surgical procedures, as well as non-sterile procedures such as those conventionally involving a core code reporter. The transcribed audio data may be analyzed to identify relevant information for documenting the clinical procedure, and a text report including the relevant information documenting the clinical procedure may be automatically generated.


Patent
Nuance Communications | Date: 2017-04-19

In accordance with aspects of the disclosure, a computing device may identify a prompt associated with an automated dialog application. An application expectation of the automated dialog application may be identified. The application expectation may comprise a structured natural language representation for a natural language response to the prompt. The computing device may receive natural language input responsive to the prompt, populate one or more data fields of the structured natural language representation with at least a portion of the natural language input, and may respond to the application expectation using the one or more data fields of the structured natural language representation.

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