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Overview of automatic stuttering recognition system

Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.

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Bibliographic Details
Main Authors: Lim, Sin Chee, Ooi, Chia Ai, Sazali, Yaacob
Other Authors: caooi@unimap.edu.my
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis 2009
Subjects:
Stuttering
Speech disorders
Stuttering recognition system
Stuttering recognition system > Design and construction
Neural networks (Computer science)
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/7338
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id my.unimap-7338
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spelling my.unimap-73382010-01-18T07:22:43Z Overview of automatic stuttering recognition system Lim, Sin Chee Ooi, Chia Ai Sazali, Yaacob caooi@unimap.edu.my Stuttering Speech disorders Stuttering recognition system Stuttering recognition system -- Design and construction Neural networks (Computer science) Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. Stuttering is a speech disorder. The flow of speech is disrupted by involuntary repetitions and prolongation of sounds, syllables, words or phrases, and involuntary silent pauses or blocks in communication. Stuttering is an interest subject of researchers from many various domains such as speech physiology & pathology, psychology, acoustic and signal analysis. Thus there are many researchers have been done previously. This paper presents an overview of previous works on automatic stuttering recognition system. Normally, classification of speech disorder is difficult and complicated. However some classification techniques associated with stuttering are commonly recognized. This paper review on classification techniques are utilized in automatic stuttering recognition for evaluating speech problem for stutterers. Some previous works discussed the different steps involved in recognizing stuttered speech from speech samples. This paper compares different classification techniques proposed by previous researchers. Classification techniques used in previous works are Artificial Neural Networks (ANNs), Hidden Markov Model (HMM) and Support Vector Machine (SVM). 2009-11-18T05:09:19Z 2009-11-18T05:09:19Z 2009-10-11 Working Paper p.5B7 1 - 5B7 6 http://hdl.handle.net/123456789/7338 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2009) Universiti Malaysia Perlis
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Stuttering
Speech disorders
Stuttering recognition system
Stuttering recognition system -- Design and construction
Neural networks (Computer science)
spellingShingle Stuttering
Speech disorders
Stuttering recognition system
Stuttering recognition system -- Design and construction
Neural networks (Computer science)
Lim, Sin Chee
Ooi, Chia Ai
Sazali, Yaacob
Overview of automatic stuttering recognition system
description Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.
author2 caooi@unimap.edu.my
author_facet caooi@unimap.edu.my
Lim, Sin Chee
Ooi, Chia Ai
Sazali, Yaacob
format Working Paper
author Lim, Sin Chee
Ooi, Chia Ai
Sazali, Yaacob
author_sort Lim, Sin Chee
title Overview of automatic stuttering recognition system
title_short Overview of automatic stuttering recognition system
title_full Overview of automatic stuttering recognition system
title_fullStr Overview of automatic stuttering recognition system
title_full_unstemmed Overview of automatic stuttering recognition system
title_sort overview of automatic stuttering recognition system
publisher Universiti Malaysia Perlis
publishDate 2009
url http://dspace.unimap.edu.my/xmlui/handle/123456789/7338
_version_ 1643788782241054720
score 13.222552

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