Screening for neurological disease using speech articulation characteristics
AssigneesUniversity of Florida Research Foundation, Inc., Board of Trustees of Michigan State University
InventorsJohn Clyde Rosenbek, Mark D. Skowronski, Rahul Shrivastav, Supraja Anand
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Abstract
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.
Claims19
A method for screening for diseases, the method comprising:
- performing a signal analysis of a speech sample received from a subject, the signal analysis comprising extracting human factor cepstral coefficients from the speech sample and identifying articulation range and articulation rate using the human factor cepstral coefficients extracted from the speech sample, and analyzing language patterns, wherein the analyzing of the language patterns comprises analyzing the language patterns to determine if an indicator of a neurological disease is present;
- determining a likelihood and type of a disease based upon the articulation range and articulation rate identified by the signal analysis of the speech sample, as well as the analyzing of the language patterns;
- and
- outputting information indicating the likelihood and type of the disease.
A system for screening for a disease, the system comprising:
- an application service provider for receiving a speech sample from a subject;
- a memory for receiving and storing the speech sample;
- and
- one or more computer-readable storage media in operable communication with the memory and having stored thereon computer-executable instructions comprising:
- a pre-processing module for receiving the speech sample from the application service provider and cleaning the speech sample or selecting segments of the speech sample for further processing;
- a speech metric module for receiving the speech sample from the pre-processing module and identifying articulation range and articulation rate using human factor cepstral coefficients;
- and
- a language marker module for receiving the speech sample from the pre-processing module and analyzing language patterns;
- a comparator for comparing the output of the speech metric module and the output of the language marker module with normative data, criteria, or previous output of the speech metric module and the language marker module stored in the memory of the system and outputting a decision indicating a likelihood of a neurological disease.
Dependencies are inferred from the claim text.