Identification of voice disorders using speech samples

Jagadish Nayak, P. Subbanna Bhat

Research output: Contribution to conferencePaper

13 Citations (Scopus)

Abstract

This paper attempts to identify pathological disorders of larynx using Wavelet Analysis. Speech samples carry symptoms of disorder in the place of their origin. The speech signal is subjected to wavelet analysis, and the coefficients are used to identify disorders such as Vocal Fold Paralysis. Multilayer Artificial Neural Network is used for classification of normal and affected signals.

Original languageEnglish
Pages951-953
Number of pages3
Publication statusPublished - 01-12-2003
Externally publishedYes
EventIEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region - Bangalore, India
Duration: 15-10-200317-10-2003

Conference

ConferenceIEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region
CountryIndia
CityBangalore
Period15-10-0317-10-03

Fingerprint

Wavelet analysis
Multilayers
Neural networks

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Nayak, J., & Bhat, P. S. (2003). Identification of voice disorders using speech samples. 951-953. Paper presented at IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region, Bangalore, India.
Nayak, Jagadish ; Bhat, P. Subbanna. / Identification of voice disorders using speech samples. Paper presented at IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region, Bangalore, India.3 p.
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Nayak, J & Bhat, PS 2003, 'Identification of voice disorders using speech samples' Paper presented at IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region, Bangalore, India, 15-10-03 - 17-10-03, pp. 951-953.

Identification of voice disorders using speech samples. / Nayak, Jagadish; Bhat, P. Subbanna.

2003. 951-953 Paper presented at IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region, Bangalore, India.

Research output: Contribution to conferencePaper

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PY - 2003/12/1

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N2 - This paper attempts to identify pathological disorders of larynx using Wavelet Analysis. Speech samples carry symptoms of disorder in the place of their origin. The speech signal is subjected to wavelet analysis, and the coefficients are used to identify disorders such as Vocal Fold Paralysis. Multilayer Artificial Neural Network is used for classification of normal and affected signals.

AB - This paper attempts to identify pathological disorders of larynx using Wavelet Analysis. Speech samples carry symptoms of disorder in the place of their origin. The speech signal is subjected to wavelet analysis, and the coefficients are used to identify disorders such as Vocal Fold Paralysis. Multilayer Artificial Neural Network is used for classification of normal and affected signals.

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Nayak J, Bhat PS. Identification of voice disorders using speech samples. 2003. Paper presented at IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region, Bangalore, India.