Paper Info
Title
Developing An Hmm-Based Speech Synthesis System For Malay: A Comparison Of Iterative And Isolated Unit Training
Abstract
The development of an HMM-based speech synthesis system for a new language requires resources like speech database and segment-phonetic labels. As an under-resourced language. Malay lacks the necessary resources for the development of such a system, especially segment-phonetic labels. This research aims at developing an HMM-based speech synthesis system for Malay. We are proposing the use of two types of training HMMs, which are the benchmark iterative training incorporating the DAEM algorithm and isolated unit training applying segment-phonetic labels of Malay. The preferred method for preparing segment-phonetic labels is the automatic segmentation. The automatic segmentation of Malay speech database is performed using two approaches which are uniform segmentation that applies fixed phone duration, and a cross-lingual approach that adopts the acoustic model of English. We have measured the segmentation error of the two segmentation approaches to ascertain their relative effectiveness. A listening test was used to evaluate the intelligibility and naturalness of the synthetic speech produced from the iterative and isolated unit training. We also compare the performance of the HMM-based speech synthesis system with existing Malay speech synthesis systems.
Year
DOI
Venue
2014
10.1587/transinf.E97.D.1273
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
Keywords
Field
DocType
iterative training, isolated unit training, cross lingual approach, uniform segmentation, segment-phonetic labels
Speech synthesis,Malay,Computer science,Speech recognition,Hidden Markov model
Journal
Volume
Issue
ISSN
E97D
5
1745-1361
Citations 
PageRank 
References 
2
0.39
23
Authors
5
Name
Order
Citations
PageRank
Mumtaz B. Mustafa151.63
Zuraidah Mohd Don2202.55
Raja Noor Ainon3577.36
Roziati Zainuddin4658.91
Gerry Knowles531.76