Department of Communication Sciences and Disorders, University of Texas at Austin, 1 University Station A1100, Austin, Texas 78712, USA.
J Acoust Soc Am. 2012 Nov;132(5):EL378-84. doi: 10.1121/1.4757729.
This study investigated the contribution of low-frequency harmonics to identifying Mandarin tones in natural and vocoded speech in quiet and noisy conditions. Results showed that low-frequency harmonics of natural speech led to highly accurate tone identification; however, for vocoded speech, low-frequency harmonics yielded lower tone identification than stimuli with full harmonics, except for tone 4. Analysis of the correlation between tone accuracy and the amplitude-F0 correlation index suggested that "more" speech contents (i.e., more harmonics) did not necessarily yield better tone recognition for vocoded speech, especially when the amplitude contour of the signals did not co-vary with the F0 contour.
本研究旨在探究低频谐波在安静和嘈杂环境下识别自然和语音编码语音中普通话声调的作用。结果表明，自然语音的低频谐波能实现高度准确的声调识别；但对于语音编码语音，低频谐波的声调识别率低于全谐波刺激，除了 4 调。对声调识别准确率与音强-基频相关指数的相关性分析表明，语音编码语音中，“更多”的语音内容（即更多谐波）并不一定能带来更好的声调识别，尤其是当信号的振幅轮廓与基频轮廓不同步时。
