2012 ©
             Publication
Journal Publication
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  
     Volume 12 
     Issue
     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
577020065-1 Mr. PONGSATHON JANYOI [Main Author]
Science Doctoral Degree

Reviewing Status มีผู้ประเมินอิสระ 
Status ตีพิมพ์แล้ว 
Level of Publication นานาชาติ 
citation false 
Part of thesis true 
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