Study of noise robustness of First Formant Bandwidth (F1BW) method
The performance of speech recognition application under adverse noisy condition often becomes the topic of researchers regardless of the language used. Applications that use vowel phonemes require high degree of Standard Malay vowel recognition capability.In Malaysia, researches in vowel recognitio...
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2011
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my.uum.repo.136242015-04-07T06:55:11Z http://repo.uum.edu.my/13624/ Study of noise robustness of First Formant Bandwidth (F1BW) method Mohd Yusof, Shahrul Azmi Siraj, Fadzilah Yaacob, S. M.P, Paulraj Nazri, Ahmad QA76 Computer software The performance of speech recognition application under adverse noisy condition often becomes the topic of researchers regardless of the language used. Applications that use vowel phonemes require high degree of Standard Malay vowel recognition capability.In Malaysia, researches in vowel recognition is still lacking especially in the usage of Malay vowels, independent speaker systems, recognition robustness and algorithm speed and accuracy. This paper presents a noise robustness study on an improved vowel feature extraction method called First Formant Bandwidth (F1BW) on three classifiers of Multinomial Logistic Regression (MLR), K-Nearest Neighbors (k-NN) and Linear Discriminant Analysis (LDA).Results show that LDA performs best in overall vowel classification compared to MLR and KNN in terms of robustness capability. 2011 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/13624/1/99%20%281%29.pdf Mohd Yusof, Shahrul Azmi and Siraj, Fadzilah and Yaacob, S. and M.P, Paulraj and Nazri, Ahmad (2011) Study of noise robustness of First Formant Bandwidth (F1BW) method. In: 3rd International Conference on Computing and Informatics (ICOCI 2011), 8-9 June 2011, Bandung, Indonesia. http://www.icoci.cms.net.my |
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QA76 Computer software Mohd Yusof, Shahrul Azmi Siraj, Fadzilah Yaacob, S. M.P, Paulraj Nazri, Ahmad Study of noise robustness of First Formant Bandwidth (F1BW) method |
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The performance of speech recognition application under adverse noisy condition often becomes the topic of researchers regardless of
the language used. Applications that use vowel phonemes require high degree of Standard Malay vowel recognition capability.In Malaysia, researches in vowel recognition is still lacking especially in the usage of Malay vowels, independent speaker systems, recognition robustness and algorithm speed and accuracy. This paper presents a noise robustness study
on an improved vowel feature extraction method called First Formant Bandwidth (F1BW) on three classifiers of Multinomial Logistic Regression
(MLR), K-Nearest Neighbors (k-NN) and Linear Discriminant Analysis (LDA).Results show that LDA performs best in overall vowel classification compared to MLR and KNN in terms of robustness capability. |
format |
Conference or Workshop Item |
author |
Mohd Yusof, Shahrul Azmi Siraj, Fadzilah Yaacob, S. M.P, Paulraj Nazri, Ahmad |
author_facet |
Mohd Yusof, Shahrul Azmi Siraj, Fadzilah Yaacob, S. M.P, Paulraj Nazri, Ahmad |
author_sort |
Mohd Yusof, Shahrul Azmi |
title |
Study of noise robustness of First Formant Bandwidth (F1BW) method |
title_short |
Study of noise robustness of First Formant Bandwidth (F1BW) method |
title_full |
Study of noise robustness of First Formant Bandwidth (F1BW) method |
title_fullStr |
Study of noise robustness of First Formant Bandwidth (F1BW) method |
title_full_unstemmed |
Study of noise robustness of First Formant Bandwidth (F1BW) method |
title_sort |
study of noise robustness of first formant bandwidth (f1bw) method |
publishDate |
2011 |
url |
http://repo.uum.edu.my/13624/1/99%20%281%29.pdf http://repo.uum.edu.my/13624/ http://www.icoci.cms.net.my |
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1644281236508639232 |
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13.211869 |