Abstract
This paper addresses the realization of a Human/Machine (H/M) interface including a system for automatic recognition of the Continuous Pathological Speech (ARSCPS) and several communication tools in order to help frail people with speech problems (Dysarthric speech) to access services providing by new technologies of information and communication (TIC) while making it easier for the doctors to achieve a first diagnosis on the patient’s disease. In addition, an ARSCPS has been improved and developed for normal and pathology voice while establishing a link with our graphic interface which is based on the box tools Hidden Markov Model Toolkit (HTK), in addition to the Hidden Models of Markov (HMM). In our work we used different techniques of feature extraction for the speech recognition system in order to improve the dysarthric speech intelligibility while developing an ARSCPS which can perform well for pathological and normal speakers. These techniques are based on the coefficients of ETSI standard Mel Frequency Cepstral Coefficient Front End (ETSI MFCC FE V2.0); Perceptual Linear Prediction coefficients (PLP); Mel Frequency Cepstral Coefficients (MFCC) and the recently proposed Power Normalized Cepstral Coefficients (PNCC) have been used as a basis for comparison. In this context we used the Nemours database which contains 11 speakers that represents dysarthric speech and 11 speakers that represents normal speech.
Highlights
An interface for the control of Automatic Recognition System of Continuous Pathological Speech (ARSCPS) [1] can be very useful for speakers with dysarthria which is a neurological disorder of speech that affects millions of people
A dysarthria man has significant difficulty in communication, according to Aronson [2]; Dysarthria [3] covers various speech disorders resulting from neurological disorders
The Nemours database is constituted by 74 sentences spoken with varying degrees of dysarthria for each one of the 11 male speakers
Summary
An interface for the control of Automatic Recognition System of Continuous Pathological Speech (ARSCPS) [1] can be very useful for speakers with dysarthria which is a neurological disorder of speech that affects millions of people. A dysarthria man has significant difficulty in communication, according to Aronson [2]; Dysarthria [3] covers various speech disorders resulting from neurological disorders. These disorders are related to the disturbance of the brain and stimulus nerves of the muscles involved in the production of speech. A pathological database NEMOURS [6] is integrated for improving the speech intelligibility of dysarthria patients.
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