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A prosodic phrasing model for a Korean text-to-speech synthesis system

机译:韩国文字转语音合成系统的韵律短语模型

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摘要

This paper presents a prosodic phrasing model for Korean to be used in a text-to-speech synthesis (TTS) system. Read text corpora were morpho-syntactically parsed and prosodically labeled following the Penn Korean Treebank (Han, Chunghye, Ko, Eon-Suk, Yi, Heejong, Palmer, M., 2002. Penn Korean Treebank: development and evaluation. In: Proceedings of the 16th Pacific Asian Conference on Language and Computation. Korean Society for Language and Information.) and K-ToBI prosodic labeling conventions (Sun-Ah, J., 2000. K-ToBI (Korean ToBI) labelling conventions. Version 3.1. Available from: URL < http:// www.linguistics.ucla.edu/people/jun/ktobi/K-tobi.html >.), respectively. Decision trees were trained with morpho-syntactic and textual distance features to predict locations of accentual and intonational phrase breaks. Our phrasing model cross-validated on a 300-sentence corpus (6936 words or 21,436 syllables, with an average of 72 syllables or 23 words per sentence) predicted non-breaks with F = 92.4% and breaks with F = 88.0% (F = 72.8% for accentual phrase breaks and F = 71.3% for intonational phrase breaks).
机译:本文提出了一种用于韩语的韵律短语模型,该模型可用于文本到语音合成(TTS)系统中。阅读文本语料库在宾州韩国树库中进行了句法语法分析和韵律标注(Han,Chunghye,Ko,Eon-Suk,Yi,Heejong,Palmer,M.,2002年。宾州韩国树库:发展和评估。在:第16届亚太语言和计算会议。韩国语言和信息学会)和K-ToBI韵律标签惯例(Sun-Ah,J.,2000年。K-ToBI(韩国ToBI)标签惯例。版本3.1。 :网址分别为。)。决策树接受了形态句法和文本距离特征的训练,以预测重音和国际语词组中断的位置。我们的词组模型在300个句子的语料库(6936个单词或21,436个音节,平均每个句子中包含72个音节或23个单词)上交叉验证,预测了F = 92.4%和F = 88.0%(F =重音词组中断为72.8%,国际性词组中断为F = 71.3%。

著录项

  • 来源
    《Computer speech and language》 |2006年第1期|p.69-79|共11页
  • 作者

    Kyuchul Yoon;

  • 作者单位

    Department of Linguistics, The Ohio State University, 1712 Neil Avenue, Columbus, OH 43210, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算技术、计算机技术;
  • 关键词

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