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Modeling tone and intonation in Mandarin and English as a process of target approximation

机译:模拟普通话和英语的语气和语调,作为目标近似的过程

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This paper reports the development of a quantitative target approximation (qTA) model for generating F-0 contours of speech. The qTA model simulates the production of tone and intonation as a process of syllable-synchronized sequential target approximation [Xu, Y. (2005). "Speech melody as articulatorily implemented communicative functions," Speech Commun. 46, 220-251]. It adopts a set of biomechanical and linguistic assumptions about the mechanisms of speech production. The communicative functions directly modeled are lexical tone in Mandarin and lexical stress in English and focus in both languages. The qTA model is evaluated by extracting function-specific model parameters from natural speech via supervised learning (automatic analysis by synthesis) and comparing the F-0 contours generated with the extracted parameters to those of natural utterances through numerical evaluation and perceptual testing. The F-0 contours generated by the qTA model with the learned parameters were very close to the natural contours in terms of root mean square error, rate of human identification of tone, and focus and judgment of naturalness by human listeners. The results demonstrate that the qTA model is both an effective tool for research on tone and intonation and a potentially effective system for automatic synthesis of tone and intonation.
机译:本文报告了用于生成语音F-0轮廓的定量目标近似(qTA)模型的开发。 qTA模型模拟音调和语调的产生,作为音节同步顺序目标逼近的过程[Xu,Y.(2005)。 “语音旋律以语音方式实现了交流功能,” Speech Commun。 46,220-251]。它采用了一系列有关语音生成机制的生物力学和语言学假设。直接建模的交流功能是普通话的词汇语调和英语的词汇重音,并且以两种语言为重点。 qTA模型是通过监督学习(通过综合自动分析)从自然语音中提取特定于功能的模型参数,并通过数值评估和感知测试将提取的参数生成的F-0轮廓与自然话语的轮廓进行比较,从而评估qTA模型的。由qTA模型生成的具有学习参数的F-0轮廓在均方根误差,人类对音调的识别率以及听众的注意力和自然性判断方面非常接近自然轮廓。结果表明,qTA模型既是研究音调和语调的有效工具,又是自动合成音调和语调的潜在有效系统。

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