On analysis of eigenpitch in Mandarin Chinese

Jilei Tian, J. Nurminen
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引用次数: 12

Abstract

Prosody is an inherent supra-segmental feature of human speech that is being employed to express, e.g., attitude, emotion, intent and attention. Pitch is the most important feature among the prosodic information. For Mandarin Chinese speech, the pitch information is even more crucial because Mandarin is a tonal language in which the tone of each syllable is described by its pitch contour. In this paper, the concept of syllable-based eigenpitch is introduced and investigated using principal component analysis (PCA). The eigenpitch and the related eigenfeatures are analyzed, and it is shown that the tonal patterns are preserved in the eigenpitch representation. Furthermore, we show that the dimension of pitch in the eigenspace can be reduced while minimizing the energy loss of the original pitch contour. Finally, we briefly discuss the quantization properties of the eigenpitch representation. We also present experimental results obtained using a Mandarin speech database. They are in line with the theoretical reasoning and further prove the usefulness of the proposed pitch modeling technique.
汉语普通话特征音分析
韵律是人类语言固有的超分段特征,被用来表达态度、情感、意图和注意等。音高是韵律信息中最重要的特征。对于普通话语音来说,音高信息更为重要,因为普通话是一种声调语言,每个音节的音调都是由它的音高轮廓来描述的。本文引入了基于音节的特征音高的概念,并用主成分分析(PCA)对其进行了研究。分析了特征音高及其相关特征,结果表明,特征音高表示中保留了音调模式。此外,我们证明了特征空间中的基音维数可以在最小化原始基音轮廓能量损失的同时被降低。最后,我们简要地讨论了特征音高表示的量化特性。我们还介绍了使用普通话语音数据库获得的实验结果。它们与理论推理一致,进一步证明了所提出的音高建模技术的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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