基于HMM的泰米尔语文本到语音合成系统

A. F. Jalin, J. Jayakumari
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引用次数: 8

摘要

TTS (text - to - speech)系统为输入的文本生成等效的语音。虽然语音生成具有中等的复杂性,但如何将说话人的表达引入自然是语音生成中面临的一大挑战。在泰米尔语中,由于其语音,用于其他语言(如英语)的算法将不起作用,因为自适应发音完全依赖于语言结构。我们提议的工作将在信号处理的TTS领域。目前的研究使用隐马尔可夫模型(HMM)作为机器学习算法进行分类,是最早的印度语单词识别系统之一。本文利用HMM对泰米尔语进行了HMM语音合成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Text to speech synthesis system for tamil using HMM
TTS (Text-To-Speech) systems generate speech equivalent for the text given as input. Though generation of speech is with moderate complexity the aspect of introducing naturality with the expression of the speaker is a big challenge faced in TTS. When in Tamil, because of its phonetics, the algorithms used for other languages like English will not work because of adaptive pronunciations which are completely dependent on the language constructs. Our proposed work will be in the TTS area of signal processing. Current researches have used HMM (A Hidden Markov model) as the machine learning algorithm for classification and is one of the first of the Indic word recognition system. In this paper, an HMM speech synthesis is done using the HMM for the Tamil language.
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