Automatic phonetic segmentation of malay speech database

This paper deals with automatic phonetic segmentation for Malay continuous speech. This study investigates fast and automatic phone segmentation in preparing database for Malay concatenative Text-to-Speech (TTS) systems. A 35 Malay phone set has been chosen, which is suitable for building Malay TTS....

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Main Authors: Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain, Tan, Tian Swee, Ariff, Ahmad Kamarul
Format: Conference or Workshop Item
Language:en
Published: 2007
Subjects:
Online Access:http://eprints.utm.my/7635/1/Sheikh_Hussain_Shaikh_2007_Automatic_Phonetic_Segmentation_of_Malay_Speech.pdf
http://eprints.utm.my/7635/
http://dx.doi.org/10.1109/ICICS.2007.4449574
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_version_ 1845471847936688128
author Ting, Chee Ming
Shaikh Salleh, Sheikh Hussain
Tan, Tian Swee
Ariff, Ahmad Kamarul
author_facet Ting, Chee Ming
Shaikh Salleh, Sheikh Hussain
Tan, Tian Swee
Ariff, Ahmad Kamarul
author_sort Ting, Chee Ming
building UTM Library
collection Institutional Repository
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
continent Asia
country Malaysia
description This paper deals with automatic phonetic segmentation for Malay continuous speech. This study investigates fast and automatic phone segmentation in preparing database for Malay concatenative Text-to-Speech (TTS) systems. A 35 Malay phone set has been chosen, which is suitable for building Malay TTS. The segmentation experiment is based on this phone set. HMM based segmentation approach which uses Viterbi force alignment technique is adapted. We use continuous density HMM (CDHMM) with Gaussian mixture which is performs well in speech recognition to prevent large segmentation errors. Besides, this paper presents an implicit boundary refinement method that is incorporated in the Viterbi phonetic alignment. In this approach, the HMM model is trained with phone tokens with their boundaries extended to the be-side phones. This increases the ability of the HMM in modeling phone boundaries and provides effect of implicit boundary refinement when used in phonetic alignment thus reduce segmentation errors. This approach improves increase the performance of baseline HMM segmentation from 42.39%, 74.83%, 84.34% of automatic boundary marks within error smaller than 5, 15, and 25ms to 47.75%, 76.38%, 85.55%.
format Conference or Workshop Item
id my.utm.eprints-7635
institution Universiti Teknologi Malaysia
language en
publishDate 2007
record_format eprints
spelling my.utm.eprints-76352010-06-01T15:54:10Z http://eprints.utm.my/7635/ Automatic phonetic segmentation of malay speech database Ting, Chee Ming Shaikh Salleh, Sheikh Hussain Tan, Tian Swee Ariff, Ahmad Kamarul TK Electrical engineering. Electronics Nuclear engineering This paper deals with automatic phonetic segmentation for Malay continuous speech. This study investigates fast and automatic phone segmentation in preparing database for Malay concatenative Text-to-Speech (TTS) systems. A 35 Malay phone set has been chosen, which is suitable for building Malay TTS. The segmentation experiment is based on this phone set. HMM based segmentation approach which uses Viterbi force alignment technique is adapted. We use continuous density HMM (CDHMM) with Gaussian mixture which is performs well in speech recognition to prevent large segmentation errors. Besides, this paper presents an implicit boundary refinement method that is incorporated in the Viterbi phonetic alignment. In this approach, the HMM model is trained with phone tokens with their boundaries extended to the be-side phones. This increases the ability of the HMM in modeling phone boundaries and provides effect of implicit boundary refinement when used in phonetic alignment thus reduce segmentation errors. This approach improves increase the performance of baseline HMM segmentation from 42.39%, 74.83%, 84.34% of automatic boundary marks within error smaller than 5, 15, and 25ms to 47.75%, 76.38%, 85.55%. 2007-12 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/7635/1/Sheikh_Hussain_Shaikh_2007_Automatic_Phonetic_Segmentation_of_Malay_Speech.pdf Ting, Chee Ming and Shaikh Salleh, Sheikh Hussain and Tan, Tian Swee and Ariff, Ahmad Kamarul (2007) Automatic phonetic segmentation of malay speech database. In: Information, Communications & Signal Processing, 2007 6th International Conference, 10-13 Dec 2007, Singapore. http://dx.doi.org/10.1109/ICICS.2007.4449574
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ting, Chee Ming
Shaikh Salleh, Sheikh Hussain
Tan, Tian Swee
Ariff, Ahmad Kamarul
Automatic phonetic segmentation of malay speech database
title Automatic phonetic segmentation of malay speech database
title_full Automatic phonetic segmentation of malay speech database
title_fullStr Automatic phonetic segmentation of malay speech database
title_full_unstemmed Automatic phonetic segmentation of malay speech database
title_short Automatic phonetic segmentation of malay speech database
title_sort automatic phonetic segmentation of malay speech database
topic TK Electrical engineering. Electronics Nuclear engineering
url http://eprints.utm.my/7635/1/Sheikh_Hussain_Shaikh_2007_Automatic_Phonetic_Segmentation_of_Malay_Speech.pdf
http://eprints.utm.my/7635/
http://dx.doi.org/10.1109/ICICS.2007.4449574
url_provider http://eprints.utm.my/