基于基频的韵律自动标记

A. Shilkov, S. Ivanov, Maxim Sipatov, V. Golodov
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引用次数: 0

摘要

韵律可以指那些代表音节和更大的语音单位的属性的语音元素。韵律还包括个别的语言功能,如节奏、重音和语调。韵律使识别说话人的声音个性或话语特征成为可能,例如说话人的情绪状态或话语风格。学习方言或语言通常需要韵律标记。本文主要研究基于语音基本频率的韵律自动标记。以基频的提取为主要挑战,综述了SOTA神经网络和更保守的算法等多种方法。应用其中一种方法后,就得到了SLAM标记。最后,比较了基于不同基频获得的标记。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Prosody Markup Based on Fundamental Frequency
Prosody can be referred to those elements of speech that represent the properties of syllables and larger units of speech. Prosody also includes individual linguistic functions such as rhythm, accent, and intonation. Prosody makes it possible to identify the speaker's vocal personality or the characteristics of utterances, such as the speaker's emotional state or the style of utterance. Studying dialects or languages often requires prosody markup. The article is devoted to automatic prosody markup based on the fundamental frequency of the utterance. With the extraction of the fundamental frequency being the main challenge multiple methods are reviewed such as SOTA neural networks and more conservative algorithms. After applying one of these methods, SLAM markup is obtained. In the end markups based on differently obtained fundamental frequencies are compared.
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