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用于辅音识别的语音波形包络线索。

Speech waveform envelope cues for consonant recognition.

作者信息

Van Tasell D J, Soli S D, Kirby V M, Widin G P

机构信息

Department of Communication Disorders, University of Minnesota, Minneapolis 55455.

出版信息

J Acoust Soc Am. 1987 Oct;82(4):1152-61. doi: 10.1121/1.395251.

Abstract

This study investigated the cues for consonant recognition that are available in the time-intensity envelope of speech. Twelve normal-hearing subjects listened to three sets of spectrally identical noise stimuli created by multiplying noise with the speech envelopes of 19(aCa) natural-speech nonsense syllables. The speech envelope for each of the three noise conditions was derived using a different low-pass filter cutoff (20, 200, and 2000 Hz). Average consonant identification performance was above chance for the three noise conditions and improved significantly with the increase in envelope bandwidth from 20-200 Hz. SINDSCAL multidimensional scaling analysis of the consonant confusions data identified three speech envelope features that divided the 19 consonants into four envelope feature groups ("envemes"). The enveme groups in combination with visually distinctive speech feature groupings ("visemes") can distinguish most of the 19 consonants. These results suggest that near-perfect consonant identification performance could be attained by subjects who receive only enveme and viseme information and no spectral information.

摘要

本研究调查了语音的时间-强度包络中可用于辅音识别的线索。12名听力正常的受试者聆听了三组频谱相同的噪声刺激,这些刺激是通过将噪声与19个(aCa)自然语音无意义音节的语音包络相乘而产生的。三种噪声条件下的语音包络分别使用不同的低通滤波器截止频率(20、200和2000赫兹)得出。三种噪声条件下的平均辅音识别表现均高于随机水平,并且随着包络带宽从20赫兹增加到200赫兹而显著提高。对辅音混淆数据进行的SINDSCAL多维缩放分析确定了三种语音包络特征,这些特征将19个辅音分为四个包络特征组(“音包组”)。音包组与视觉上独特的语音特征分组(“视位组”)相结合,可以区分19个辅音中的大多数。这些结果表明,仅接收音包组和视位组信息而不接收频谱信息的受试者可以实现近乎完美的辅音识别表现。

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