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Reseach Article

Performance Evaluation of Speech Synthesis Techniques for Marathi Language

by Sangramsing Kayte, Monica Mundada, Charansing Kayte
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 130 - Number 3
Year of Publication: 2015
Authors: Sangramsing Kayte, Monica Mundada, Charansing Kayte
10.5120/ijca2015907023

Sangramsing Kayte, Monica Mundada, Charansing Kayte . Performance Evaluation of Speech Synthesis Techniques for Marathi Language. International Journal of Computer Applications. 130, 3 ( November 2015), 45-50. DOI=10.5120/ijca2015907023

@article{ 10.5120/ijca2015907023,
author = { Sangramsing Kayte, Monica Mundada, Charansing Kayte },
title = { Performance Evaluation of Speech Synthesis Techniques for Marathi Language },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 130 },
number = { 3 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 45-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume130/number3/23193-2015907023/ },
doi = { 10.5120/ijca2015907023 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:24:14.812248+05:30
%A Sangramsing Kayte
%A Monica Mundada
%A Charansing Kayte
%T Performance Evaluation of Speech Synthesis Techniques for Marathi Language
%J International Journal of Computer Applications
%@ 0975-8887
%V 130
%N 3
%P 45-50
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Text to speech synthesis (TTS) is the production of artificial speech by a machine for the given text as input. The speech synthesis can be achieved by concatenation and Hidden Markov Model techniques. The voice synthesized by these techniques should be evaluated for quality. The study extends towards the comparative analysis for quality of speech synthesis using hidden markov model and unit selection approach. The quality of synthesized speech is analyzed for subjective measurement using mean opinion score and objective measurement based on mean square score and peak signal-to-noise ratio (PSNR). The quality is also accessed by Mel-frequency cepstral coefficient features for synthesized speech. The experimental analysis shows that unit selection method results in better synthesized voice than hidden markov model.

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Index Terms

Computer Science
Information Sciences

Keywords

Keyword TTS MOS HMM Unit Selection Mean Variance.