A Novel Text-to-Speech Synthesis System Using Syllable-Based HMM for Tamil Language

被引：1

作者：

Manoharan, J. Samuel ^{[1
]}

机构：

[1] Sir Isaac Newton Coll Engn & Technol, Dept ECE, Nagapattinam, India

来源：

PROCEEDINGS OF SECOND INTERNATIONAL CONFERENCE ON SUSTAINABLE EXPERT SYSTEMS (ICSES 2021) | 2022年 / 351卷

关键词：

Text-to-speech conversion; Natural language processing; Human perception; Tamil language database; Hidden Markov model;

D O I：

10.1007/978-981-16-7657-4_26

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A text-to-speech (TTS) is an intellectual system that converts the given language text into speech output. TTS system synthesizer can be evaluated using different aspects such as naturalness, ability of expressing intelligence, preference of synthetic speech, and some of the human perception factors like comprehensibility. TTS system is used in many application areas where the human assistance is to be removed. For example, the TTS program allows people with visual impairments or reading disabilities to listen to written words on a home computer. TTS system for Tamil language has the complexity of adaptive pronunciations that are dependent on the language constructs. This paper introduces a hidden Markov model (HMM)-based speech synthesis for Tamil language.

引用

页码：305 / 314

页数：10

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