University of Florida Research Foundation, Incorporated

Michigan State University

Cochlear Limited

Mark D Skowronski

Rahul Shrivastav

Lee Krause

John Clyde Rosenbek

Supraja Anand

Bonny Banerjee

Alice Holmes

James Russell Bress

George Shenoda

James Proctor

Detection of neurological diseases such as Parkinson's disease can be accomplished through analyzing a subject's speech for acoustic measures based on human factor cepstral coefficients (HFCC). Upon receiving a speech sample from a subject, a signal analysis can be performed that includes identifying articulation range and articulation rate using HFCC and delta coefficients. A likelihood of Parkinson's disease, for example, can be determined based upon the identified articulation range and articulation rate of the speech.

Screening for neurological disease using speech articulation characteristics

A tuning system for tuning a speech recognition system includes a transmitter for sending a user response to a speech recognition system. The user response is based at least in part on a test stimulus that may be generated by the control system. A receiver receives a recognized response from the speech recognition system; this recognized response is based at least in part on the associated user response. An adjustment module adjusts at least one parameter of the speech recognition system based at least in part on at least one of the test stimulus, the associated user response, and the recognized response.

Systems and methods for tuning automatic speech recognition systems

A network based processing element for processing audio information improves the understanding of speech or music for intended listeners based on an identifier. The processing involves performing a media enhancement function, where a parameter affecting the utilization or performance aspects of the media enhancement function are dependent upon the identifier. A 'media enhancement server' (MES) is included, whereby the audio of a telephone call, video call, multimedia program or other stream to be heard by a specific listener is processed using a personalized audio enhancement parameter to enhance the audio signal such that the listener will enjoy a benefit, such as better comprehension of the information, reduced listening effort, and more listening comfort during the call. The personalized parameters are stored and retrieved based upon the identifier, and used within the MES. The audio portion of the call or stream could be speech, music, or a combination.

Network based media enhancement function based on an identifier

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Okemos, MI, United States of America

Mark D Skowronski