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WordNet Based Sindhi Text to Speech Synthesis System

机译:基于WordNet的信德语语音合成系统

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The text-to-speech (TTS) synthesis technology enables machine to convert text into audible speech and used throughout the world to enhance the accessibility of the information. The important component of any TTS synthesis system is the database of sounds. In this study, three types of sound units i.e., phonemes, diphones and syllables are concatenated to produce natural sound for good quality Sindhi text to speech (STTS) system. The object of this paper consists in treating the phonemes, diphones and syllables under the aspect of the lexicon. The methodology used in STTS is to exploit acoustic representations of speech for synthesis, together with linguistic analyses of text. Sindhi is highly homographic language, the text is written without diacritics in real life applications, that creates lexical and morphological ambiguity. The problem of understating non-diacritic words can be solved using semantic knowledge. This paper describes a Sindhi TTS synthesis system that relies on a WordNet to identify the analogical relations between words in the text. The proposed approach is focused on the use of WordNet structures for the task of synthesis. The architecture and novel algorithm for STTS is proposed. The experiments using WordNet that show promising results and the accuracy of our proposed approach is acceptable.
机译:文本语音转换(TTS)合成技术使机器能够将文本转换为可听语音,并在全世界范围内得到使用,以增强信息的可访问性。任何TTS合成系统的重要组成部分都是声音数据库。在这项研究中,将三种类型的声音单元(即音素,双音素和音节)组合在一起,以产生自然的声音,从而获得高质量的信德文本语音转换(STTS)系统。本文的目的在于从词典的角度来处理音素,双音素和音节。 STTS中使用的方法是利用语音的声学表示进行合成,以及对文本进行语言分析。信德语是一种高度同源的语言,在现实生活中使用的文字没有变音符号,从而造成词汇和形态上的歧义。可以使用语义知识解决低估非音素词的问题。本文介绍了一种依靠WordNet来识别文本中单词之间的类比关系的Sindhi TTS综合系统。所提出的方法着重于将WordNet结构用于综合任务。提出了STTS的体系结构和新算法。使用WordNet进行的实验显示出令人鼓舞的结果,并且我们提出的方法的准确性是可以接受的。

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