M
Michael J. Newman
Researcher at Nuance Communications
Publications - 28
Citations - 1931
Michael J. Newman is an academic researcher from Nuance Communications. The author has contributed to research in topics: Speaker recognition & Voice activity detection. The author has an hindex of 18, co-authored 27 publications receiving 1915 citations. Previous affiliations of Michael J. Newman include Princeton University.
Papers
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Patent
Error correction in speech recognition
Daniell Stevens,Robert Roth,Joel M. Gould,Michael J. Newman,Dean Sturtevant,Charles E. Ingold,David Abrahams,Allan Gold +7 more
TL;DR: In this paper, new techniques and systems may be implemented to improve error correction in speech recognition systems, which may be used in a standard desktop environment, in a mobile environment, or in any other type of environment that can receive and/or present recognized speech.
Patent
Error correction in speech recognition by correcting text around selected area
Daniell Stevens,Robert Roth,Joel M. Gould,Michael J. Newman,Dean Sturtevant,Charles E. Ingold,David Abrahams,Allan Gold +7 more
TL;DR: In this article, a first recognition correction is produced based on a comparison between a first alternative transcript and the recognized utterance, and a second correction is generated by comparing a second alternative transcript with the first one.
Patent
Embedded system for construction of small footprint speech recognition with user-definable constraints
TL;DR: In this paper, the authors present techniques and methods that enable a voice trigger that wakes up an electronic device or causes the device to make additional voice commands active, without manual initiation of voice command functionality.
Patent
Configurable speech recognition system using multiple recognizers
TL;DR: In this article, the results of the local and remote speech recognition engines are combined based, at least in part, on logic stored by one or more components of the client/server architecture.
Patent
Sequential, nonparametric speech recognition and speaker identification
TL;DR: In this article, a speech sample is received and speech recognition is performed on the speech sample to produce recognition results, and the recognition results are evaluated in view of the training data and the identification of the speech elements to which the portions of training data are related.