Modeling tones in continuous Cantonese speech
Modeling tones in continuous Cantonese speech
复制标题
连续粤语语音的声调建模
DOI：
10.21437/icslp.2002-105
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发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Yujia Li
中科院分区：
文献类型：
--
作者：
Tan Lee;G. Kochanski;Chilin Shih;Yujia Li
粤语是一种主要的汉语方言，声调系统复杂。本文主要研究粤语声调的定量建模。它使用Stem-ML，一种独立于语言的定量语调建模和生成框架。建立一组F0预测模型，并在声学数据上进行训练。预测误差约为11 Hz的1 kHz。根据语言知识分析得到的最优模型参数。主要观察结果包括：（1）单独建模入声没有明显的优势。它们可以被认为是非入声调的简单截断版本;（2）粤语似乎有一个下降的短语语调;（3）在一个短语或一个句子的开头位置的声调往往比在最后位置的声调具有更大的韵律强度;（4）实词比虚词强;（5）长词比短词强。
Cantonese is a major Chinese dialect with a complicated tone system. This research focuses on quantitative modeling of Cantonese tones. It uses Stem-ML, a language-independent framework for quantitative intonation modeling and generation. A set of F0 prediction models are built, and trained on acoustic data. The prediction error is about 11 Hz of 1 semitone. The resulting optimal model parameters are analyzed in accordance with linguistic knowledge. Key observations include: (1) There is no obvious advantage to model the entering tones separately. They can be considered as simply truncated versions of the non-entering tones; (2) Cantonese appears to have a declining phrase intonation; (3) Tones at initial positions of a phrase or a sentence tend to have a greater prosodic strength than those at the final positions; (4) Content words are stronger than function words; (5) Long words are stronger than short words.