Identification of voice disorders using speech samples

Jagadish Nayak; P. Subbanna Bhat

Identification of voice disorders using speech samples

Jagadish Nayak^*, P. Subbanna Bhat

^*Corresponding author for this work

Research output: Contribution to conference › Paper › peer-review

15 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 language	English
Pages	951-953
Number of pages	3
Publication status	Published - 01-12-2003
Externally published	Yes
Event	IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region - Bangalore, India Duration: 15-10-2003 → 17-10-2003

Conference

Conference	IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region
Country/Territory	India
City	Bangalore
Period	15-10-03 → 17-10-03

All Science Journal Classification (ASJC) codes

Computer Science Applications
Electrical and Electronic Engineering

Cite this

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title = "Identification of voice disorders using speech samples",

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.",

author = "Jagadish Nayak and Bhat, {P. Subbanna}",

year = "2003",

month = dec,

day = "1",

language = "English",

pages = "951--953",

note = "IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region ; Conference date: 15-10-2003 Through 17-10-2003",

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TY - CONF

T1 - Identification of voice disorders using speech samples

AU - Nayak, Jagadish

AU - Bhat, P. Subbanna

PY - 2003/12/1

Y1 - 2003/12/1

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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UR - http://www.scopus.com/inward/citedby.url?scp=2342495763&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:2342495763

SP - 951

EP - 953

T2 - IEEE TENCON 2003: Conference on Convergent Technologies for the Asia-Pacific Region

Y2 - 15 October 2003 through 17 October 2003

ER -

Identification of voice disorders using speech samples

Abstract

Conference

All Science Journal Classification (ASJC) codes

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