Vocollect, Inc.

University of Pittsburgh

Vococollect, Inc.

Amro El-Jaroudi

Keith Braho

Jeffrey Pike

Lori Pike

Michael Laughery

Mingui Sun

Roger Graham Byford

Ervin Sejdic

Zhi-Hong Mao

James Coyle

Thomas S Kerr

Joshua Dudik

Jeffrey Piki

A method of classifying a swallow of a subject includes obtaining vibration data that is based on and indicative of a number of vibrations resulting from the swallow, and using a computer implemented deep learning classifier to classify the swallow based on the vibration data. Also, a system for classifying a swallow of a subject includes a computing device implementing a deep learning classifier. The computing device includes a processor apparatus structured and configured to receive vibration data that is based on and indicative of a number of vibrations resulting from the swallow, and use the deep learning classifier to classify the swallow based on the vibration data. The deep learning classifier may comprise a single layer or a multi-layer Deep Belief network.

Deep learning for classification of swallows

A speech recognition system receives and analyzes speech input from a user in order to recognize and accept a response from the user. Under certain conditions, information about the response expected from the user may be available. In these situations, the available information about the expected response is used to modify the behavior of the speech recognition system by taking this information into account. The modified behavior of the speech recognition system comprises adjusting the rejection threshold when speech input matches the predetermined expected response.

Method and system for considering information about an expected response when performing speech recognition

A speech recognition system receives and analyzes speech input from a user in order to recognize and accept a response from the user. Under certain conditions, information about the response expected from the user may be available. In these situations, the available information about the expected response is used to modify the behavior of the speech recognition system by taking this information into account. The modified behavior of the speech recognition system according to the invention has several embodiments including: comparing the observed speech features to the models of the expected response separately from the usual hypothesis search in order to speed up the recognition system; modifying the usual hypothesis search to emphasize the expected response; updating and adapting the models when the recognized speech matches the expected response to improve the accuracy of the recognition system.

A wireless device for use with speech recognition applications comprises a frame generator for generating successive frames from digitized original audio signals, the frames representing portions of the digitized audio signals. An autocorrelation circuit generates a set of coefficients for each frame, the coefficient set being reflective of spectral characteristics of the audio signal portion represented by the frame. In one embodiment, the autocorrelation coefficients may be used to predict the original audio signal to be subtracted from the original audio signals and to generate residual signals A Bluetooth transceiver is configured for transmitting the set of coefficients and/or residual signals as data to another device, which utilizes the coefficients for speech applications.

Wireless headset and method for robust voice data communication

A method for assessing a performance of a speech recognition system may include determining a grade, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words, wherein the grade indicates a level of the performance of the system and the grade is based on a recognition rate and at least one recognition factor. An apparatus for assessing a performance of a speech recognition system may include a processor that determines a grade, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words, wherein the grade indicates a level of the performance of the system and wherein the grade is based on a recognition rate and at least one recognition factor.

Methods and systems for assessing and improving the performance of a speech recognition system

Method and apparatus for determining a corrective action for a speech recognition system based on the performance of the system

Methods and systems for considering information about an expected response when performing speech recognition

Growing community of inventors

Pittsburgh, PA, United States of America

Amro El-Jaroudi