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Classification and analysis of speech abnormalities Classification et analyses des anomalies de la parole

Nayak, J and Bhat, PS and Acharya, R and Aithal, Venkataraja U (2005) Classification and analysis of speech abnormalities Classification et analyses des anomalies de la parole. ITBM-RBM, 26. pp. 319-327. ISSN 1297-9562

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Abstract

Analysis of speech has become a popular non-invasive tool for assessing the speech abnormalities. Acoustic nature of the abnormal speech gives relevant information about the type of disorder in the speech production system. These signals are essentially non-stationary; may contain indicators of current disease, or even warnings about impending diseases. The indicators may be present at all times or may occur at random—during certain intervals of the day. However, to study and pinpoint abnormalities in voluminous data collected over several hours is strenuous and time consuming. Therefore, computer based analytical tools for in-depth study and classification of data over daylong intervals can be very useful in diagnostics. This paper deals with the classification of certain diseases using artificial neural network, and then analyzed. This analysis is carried out using continuous wavelet transformation patterns. The results for various types of subjects discussed in detail and it is evident that the classifier presented in this paper has a remarkable efficiency in the range of 80–85% of accuracy.

Item Type: Article
Uncontrolled Keywords: Neural networks; Wavelet transforms; Speech; Voice pathology ; Mots clés : Réseaux neuronaux ; Transformées en odelettes ; Analyse de la parole ; Pathologies vocales
Subjects: Allied Health > MCOAHS Manipal > Speech and Hearing
Depositing User: KMC Manipal
Date Deposited: 02 Jun 2012 06:18
Last Modified: 11 Jun 2012 10:38
URI: http://eprints.manipal.edu/id/eprint/76573

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