Nuance Communications, Inc.

Microsoft Technology Licensing, LLC

Kurzweil Applied Intelligence, Inc.

Cerence Operating Company

Lernout & Hauspie Speech Products N.v.

Larnout & Hauspie Speech Products N.v.

William F Ganong, Iii

Robert Fleming

Raghu Vemula

Vladimir Sejnoha

Uwe Helmut Jost

Paul Joseph Vozila

Dushyant Sharma

Daniel Willett

Paul Adrian Van Mulbregt

Glen Edward Wilson

Patrick A Naylor

Shreedhar Madhavapeddi

Joel Praveen Pinto

George Zavaliagkos

David Alun James

Kevin R Farrell

Jianxiong Wu

Zhong Su

Jian Ye Chen

Wen Liu

Yong Qin

Zhiwei Shuang

Qin Shi

Shenghua Bao

Guido Remi Marcel Gallopyn

Jeremy Martin Jancsary

David Nahamoo

Jan Kleindienst

Nils Lenke

Martin Labsky

Jan Curin

Ljubomir Milanovic

Nathan M Bodenstab

Peter R Stubley

Gunnar Evermann

Gary B Clayton

Jerry K Carter

Jean-Guy E Dahan

Tomas Macek

Maximilian Bisani

Weiying Li

Stuart Merrill Shieber

David Mark Krowitz

Vincent Pollet

Ding Liu

Marc W Regan

Stephen W Laverty

Carl Benjamin Quillen

John Armstrong, Iii

Steven A Hatch

Shilei Zhang

Philip Charles Woodland

Marcel Katz

Syed Raza Shahid

Yik-Cheung Tam

Donald Bryant Selesky

Harley M Rosnow

Girija Yegnanarayanan

Brian Wilson

Hugo Van Hamme

Ramesh Sarukkai

Manfred Grabherr

Jean-Francois Beaumont

Brian H Wilson

Andrew Johnathon Daborn

Filip Van Aelten

Michel Boekestein

Bryan A Bentz

Rafael Jose Baptista

William F Bauer

Daniel Sevush

Joel A Feldman

Scott Bradner

Gary David Cook

Eric Montague

Steven Hoskins

Douglas Napoleone

Victor S Chen

A method, computer program product, and computing system for determining a plurality of transfer functions for a plurality of corresponding segments from a reference recording and a suspect recording. A delta transfer function between the plurality of transfer functions of a pair of corresponding segments of the plurality of corresponding segments is determined. A recording comparison confidence score is generated for the pair of corresponding segments based upon, at least in part, the delta transfer function. The suspect recording is verified based upon, at least in part, the plurality of recording comparison confidence scores.

System and method for acoustic channel identification-based data verification

A method, computer program product, and computing system for receiving an input speech signal. A transcription of the input speech signal may be generated via an automated speech recognition (ASR) system. One or more splitting points between one or more sensitive content portions and one or more non-sensitive content portions from the transcription may be identified. The input speech signal maybe split into the one or more sensitive content portions and the one or more non-sensitive content portions based upon, at least in part, the one or more splitting points, thus defining one or more sensitive content signals and one or more non-sensitive content signals.

System and method for secure transcription generation

A method, computer program product, and computing system for processing audio information associated with a speech processing system and encoding a watermark in a non-disruptive portion of the audio information.

System and method for watermarking audio data for automated speech recognition (ASR) systems

A method, computer program product, and computing system for receiving an input speech signal. A transcription of the input speech signal may be received. One or more sensitive content portions may be identified from the transcription of the input speech signal. The one or more sensitive content portions from the transcription of the input speech signal may be obscured, thus defining an obscured transcription of the input speech signal. An obscured speech signal may be generated based upon, at least in part, the input speech signal, the transcription of the input speech signal, and the obscured transcription of the input speech signal.

A method, computer program product, and computing system for: monitoring a meeting between a patient and a medical entity during a medical encounter; gathering information during the medical encounter, thus generating gathered encounter information, wherein the gathered encounter information includes video-based content of the patient; generating video-based content information via artificial intelligence, wherein the video-based content information is based at least in part upon the video-based content and/or the gathered encounter information and is configured to provide guidance to the medical entity concerning the video-based content; and providing the video-based content information to the medical entity.

Medical intelligence system and method

A method, computer program product, and computing system for: monitoring a meeting between a patient and a medical entity during a telehealth medical encounter; gathering information during the telehealth medical encounter, thus generating gathered encounter information; and rendering an informational window concerning the telehealth medical encounter for review by the patient and/or the medical entity, wherein the informational window is configured to provide supplemental information based, at least in part, upon the gathered encounter information.

A method, computer program product, and computing system for: monitoring a meeting between a patient and a medical entity during a medical encounter; gathering information during the medical encounter, thus generating gathered encounter information; generating medical encounter topical information via artificial intelligence, wherein the medical encounter topical information is based at least in part upon the gathered encounter information and is configured to provide guidance to the medical entity concerning one or more topics to be discussed during the medical encounter; and providing the medical encounter topical information to the medical entity.

A method, computer program product, and computing system for defining a model representative of a plurality of acoustic variations to a speech signal, thus defining a plurality of time-varying spectral modifications. The plurality of time-varying spectral modifications may be applied to a reference signal using a filtering operation, thus generating a time-varying spectrally-augmented signal.

System and method for data augmentation and speech processing in dynamic acoustic environments

Methods and apparatus for selectively performing speech processing in a hybrid speech processing system. The hybrid speech processing system includes at least one mobile electronic device and a network-connected server remotely located from the at least one mobile electronic device. The mobile electronic device is configured to use an embedded speech recognizer to process at least a portion of input audio to produce recognized text. A controller on the mobile electronic device determines whether to send information from the mobile electronic device to the server for speech processing. The determination of whether to send the information is based, at least in part, on an analysis of the input audio, the recognized text, or a semantic category associated with the recognized text.

Methods and apparatus for hybrid speech recognition processing

A method, computer program product, and computing system for receiving one or more inputs indicative of at least one of: a relative location of a speaker and a microphone array, and a relative orientation of the speaker and the microphone array. One or more reference signals may be received. A speech processing system may be trained using the one or more inputs and the one or more reference signals.

A method, computer program product, and computing system for initiating a session within an ACI platform; receiving an authentication request from a requester; and authenticating that the requester has the authority to access the ACI platform.

Ambient cooperative intelligence system and method

A method, computer program product, and computing system for defining model representative of a plurality of acoustic variations to a speech signal, thus defining a plurality of time-varying spectral modifications. The plurality of time-varying spectral modifications may be applied to a plurality of feature coefficients of a target domain of a reference signal, thus generating a plurality of time-varying spectrally-augmented feature coefficients of the reference signal.

According to some aspects, a method of monitoring an acoustic environment of a mobile device, at least one computer readable medium encoded with instructions that, when executed, perform such a method and/or a mobile device configured to perform such a method is provided. The method comprises receiving acoustic input from the environment of the mobile device while the mobile device is operating in the low power mode, detecting whether the acoustic input includes a voice command based on performing a plurality of processing stages on the acoustic input, wherein at least one of the plurality of processing stages is performed while the mobile device is operating in the low power mode, and using at least one contextual cue to assist in detecting whether the acoustic input includes a voice command.

Methods and apparatus for detecting a voice command

A method for removing private data from an acoustic model includes capturing speech from a large population of users, creating a text-to-speech voice from at least a portion of the large population of users, discarding speech data from a database of speech, creating text-to-speech waveforms from the text-to-speech voice and the new database of speech with the discarded speech data and generating an automatic speech recognition model using the text-to-speech waveforms.

System and method using parameterized speech synthesis to train acoustic models

In some embodiments, recognition results produced by a speech processing system (which may include two or more recognition results, including a top recognition result and one or more alternative recognition results) based on an analysis of a speech input, are evaluated for indications of potential errors. In some embodiments, the indications of potential errors may include discrepancies between recognition results that are meaningful for a domain, such as medically-meaningful discrepancies. The evaluation of the recognition results may be carried out using any suitable criteria, including one or more criteria that differ from criteria used by an ASR system in determining the top recognition result and the alternative recognition results from the speech input. In some embodiments, a recognition result may additionally or alternatively be processed to determine whether the recognition result includes a word or phrase that is unlikely to appear in a domain to which speech input relates.

Detecting potential significant errors in speech recognition results

Growing community of inventors

Brookline, MA, United States of America

William F Ganong, Iii