A novel method for blind segmentation of Thai continuous speech

S. Potisuk
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引用次数: 1

Abstract

This paper describes an acoustical investigation on Thai speech segmentation using a combination of average level crossing rate (ALCR) and root-mean-square (RMS) energy. Simple and easy to compute, ALCR information alone was successfully used in an automatic speech segmentation system for English. However, ALCR has never been applied to Thai. As a result, the objective of the study is to apply ALCR information to ascertain its usefulness in detecting significant temporal changes in continuous Thai Speech. An experiment was conducted on a small speech corpus containing 21 sentences. Preliminary results suggest that ALCR and RMS energy can be used to detect the phonetic boundary between obstruent initial consonant and preceding/following vowel. In addition, it can also be used to detect boundary between final consonant of the preceding syllable and initial consonant of the following syllable except for the case involving two successive non-identical nasals. The overall accuracy is around 81% for data from four speakers.
一种新的泰语连续语音盲分割方法
本文描述了使用平均水平交叉率(ALCR)和均方根能量(RMS)相结合的方法对泰语语音分割的声学研究。ALCR信息简单、易于计算,成功地应用于英语语音自动分词系统中。然而,ALCR从未适用于泰语。因此,本研究的目的是应用ALCR信息来确定其在检测连续泰语中显著的时间变化方面的有用性。在一个包含21个句子的小语料库上进行了实验。初步结果表明,ALCR和RMS能量可以用来检测阻塞的初始辅音和前/后元音之间的语音边界。此外,它也可以用来检测前一个音节的末辅音和后一个音节的首辅音之间的边界,但涉及两个连续的不相同的鼻音的情况除外。对于来自四个扬声器的数据,总体准确率约为81%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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