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Publication
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Title of Article |
Isarn Dialect Speech Synthesis using HMM with syllable-context features |
Date of Acceptance |
2 November 2018 |
Journal |
Title of Journal |
ECTI Transactions on Computer and Information Technology (ECTI-CIT) |
Standard |
SCOPUS |
Institute of Journal |
The Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI) Association |
ISBN/ISSN |
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Volume |
12 |
Issue |
2 |
Month |
November |
Year of Publication |
2018 |
Page |
81-89 |
Abstract |
This paper describes the Isarn speech synthesis system, which is a regional dialect spoken in the Northeast of Thailand. In this study, we focus to improve the prosody generation of the system by using the additional context features. In order to develop the system, the speech parameters (Mel-ceptrum and fundamental frequencies of phoneme within different phonetic contexts) were modelled using Hidden Markov Models (HMM). Synthetic speech was generated by converting the input text into context-dependent phonemes. Speech parameters were generated from the trained HMM, according to the context-dependent phonemes, and were then synthesized through a speech vocoder. In this study, systems were trained using three different feature sets: basic contextual features, tonal, and syllable-context features. Objective and subjective tests were conducted to determine the performance of the proposed system. The results indicated that the addition of the syllable-context features significantly improved the naturalness of synthesized speech. |
Keyword |
Text-to-speech, speech synthesis, HMM, Isarn |
Author |
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Reviewing Status |
มีผู้ประเมินอิสระ |
Status |
ตีพิมพ์แล้ว |
Level of Publication |
นานาชาติ |
citation |
false |
Part of thesis |
true |
Attach file |
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Citation |
0
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