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Classification of speech dysfluencies using LPC based parameterization techniques

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Main Authors: Hariharan, Muthusamy, Lim, Sin Chee, Ooi, Chia Ai, Sazali, Yaacob, Prof. Dr.
Other Authors: hari@unimap.edu.my
Format: Article
Language:English
Published: Springer Science+Business Media, LLC. 2011
Subjects:
Stuttering
Linear Predictive Coefficients (LPC)
Linear Prediction Cepstral Coefficients (LPCC)
Weighted Linear Prediction Cepstral Coefficients (WLPCC)
k-nearest neighbour (kNN)
Linear Discriminant Analysis (LDA)
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/12088
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spelling my.unimap-120882011-05-25T02:22:05Z Classification of speech dysfluencies using LPC based parameterization techniques Hariharan, Muthusamy Lim, Sin Chee Ooi, Chia Ai Sazali, Yaacob, Prof. Dr. hari@unimap.edu.my Stuttering Linear Predictive Coefficients (LPC) Linear Prediction Cepstral Coefficients (LPCC) Weighted Linear Prediction Cepstral Coefficients (WLPCC) k-nearest neighbour (kNN) Linear Discriminant Analysis (LDA) Link to publisher's homepage at http://www.springerlink.com/ The goal of this paper is to discuss and compare three feature extraction methods: Linear Predictive Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC) and Weighted Linear Prediction Cepstral Coefficients (WLPCC) for recognizing the stuttered events. Speech samples from the University College London Archive of Stuttered Speech (UCLASS) were used for our analysis. The stuttered events were identified through manual segmentation and were used for feature extraction. Two simple classifiers namely, k-nearest neighbour (kNN) and Linear Discriminant Analysis (LDA) were employed for speech dysfluencies classification. Conventional validation method was used for testing the reliability of the classifier results. The study on the effect of different frame length, percentage of overlapping, value of ã in a first order pre-emphasizer and different order p were discussed. The speech dysfluencies classification accuracy was found to be improved by applying statistical normalization before feature extraction. The experimental investigation elucidated LPC, LPCC and WLPCC features can be used for identifying the stuttered events and WLPCC features slightly outperforms LPCC features and LPC features. 2011-05-25T02:22:05Z 2011-05-25T02:22:05Z 2011-01-20 Article Journal of Medical Systems, 2011, pages 1-10 0148-5598 http://www.springerlink.com/content/g43486g624ux706m/ http://hdl.handle.net/123456789/12088 en Springer Science+Business Media, LLC.
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
Linear Predictive Coefficients (LPC)
Linear Prediction Cepstral Coefficients (LPCC)
Weighted Linear Prediction Cepstral Coefficients (WLPCC)
k-nearest neighbour (kNN)
Linear Discriminant Analysis (LDA)
spellingShingle Stuttering
Linear Predictive Coefficients (LPC)
Linear Prediction Cepstral Coefficients (LPCC)
Weighted Linear Prediction Cepstral Coefficients (WLPCC)
k-nearest neighbour (kNN)
Linear Discriminant Analysis (LDA)
Hariharan, Muthusamy
Lim, Sin Chee
Ooi, Chia Ai
Sazali, Yaacob, Prof. Dr.
Classification of speech dysfluencies using LPC based parameterization techniques
description Link to publisher's homepage at http://www.springerlink.com/
author2 hari@unimap.edu.my
author_facet hari@unimap.edu.my
Hariharan, Muthusamy
Lim, Sin Chee
Ooi, Chia Ai
Sazali, Yaacob, Prof. Dr.
format Article
author Hariharan, Muthusamy
Lim, Sin Chee
Ooi, Chia Ai
Sazali, Yaacob, Prof. Dr.
author_sort Hariharan, Muthusamy
title Classification of speech dysfluencies using LPC based parameterization techniques
title_short Classification of speech dysfluencies using LPC based parameterization techniques
title_full Classification of speech dysfluencies using LPC based parameterization techniques
title_fullStr Classification of speech dysfluencies using LPC based parameterization techniques
title_full_unstemmed Classification of speech dysfluencies using LPC based parameterization techniques
title_sort classification of speech dysfluencies using lpc based parameterization techniques
publisher Springer Science+Business Media, LLC.
publishDate 2011
url http://dspace.unimap.edu.my/xmlui/handle/123456789/12088
_version_ 1643790035020939264
score 13.214268

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