首页> 外文会议>38th Annual Meeting of the Association for Computational Linguistics, Oct 1-8, 2000, Hong Kong >Inducing Probabilistic Syllable Classes Using Multivariate Clustering
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Inducing Probabilistic Syllable Classes Using Multivariate Clustering

机译:使用多元聚类归纳概率音节类

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摘要

An approach to automatic detection of syllable structure is presented. We demonstrate a novel application of EM-based clustering to multivariate data, exemplified by the induction of 3- and 5-dimensional probabilistic syllable classes. The qualitative evaluation shows that the method yields phonologically meaningful syllable classes. We then propose a novel approach to grapheme-to-pho-neme conversion and show that syllable structure represents valuable information for pronunciation systems.
机译:提出了一种自动检测音节结构的方法。我们演示了基于EM的聚类对多元数据的新颖应用,以3维和5维概率音节类的归纳为例。定性评估表明,该方法产生了语音上有意义的音节类别。然后,我们提出了一种将音素转换成音素的新颖方法,并表明音节结构代表了语音系统的宝贵信息。

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