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塞音辅音和声学标志对噪声环境下语音识别的贡献。

The contribution of obstruent consonants and acoustic landmarks to speech recognition in noise.

作者信息

Li Ning, Loizou Philipos C

机构信息

Department of Electrical Engineering, University of Texas at Dallas, Richardson, Texas 75083-0688, USA.

出版信息

J Acoust Soc Am. 2008 Dec;124(6):3947. doi: 10.1121/1.2997435.

Abstract

The obstruent consonants (e.g., stops) are more susceptible to noise than vowels, raising the question whether the degradation of speech intelligibility in noise can be attributed, at least partially, to the loss of information carried by obstruent consonants. Experiment 1 assesses the contribution of obstruent consonants to speech recognition in noise by presenting sentences containing clean obstruent consonants but noise-corrupted voiced sounds (e.g., vowels). Results indicated substantial (threefold) improvement in speech recognition, particularly at low signal-to-noise ratio levels (-5 dB). Experiment 2 assessed the importance of providing partial information, within a frequency region, of the obstruent-consonant spectra while leaving the remaining spectral region unaltered (i.e., noise corrupted). Access to the low-frequency (0-1000 Hz) region of the clean obstruent-consonant spectra was found to be sufficient to realize significant improvements in performance and that was attributed to improvement in transmission of voicing information. The outcomes from the two experiments suggest that much of the improvement in performance must be due to the enhanced access to acoustic landmarks, evident in spectral discontinuities signaling the onsets of obstruent consonants. These landmarks, often blurred in noisy conditions, are critically important for understanding speech in noise for better determination of the syllable structure and word boundaries.

摘要

塞音(如爆破音)比元音更容易受到噪声的影响,这就引发了一个问题:在噪声环境中语音清晰度的下降是否至少部分可归因于塞音所携带信息的丢失。实验1通过呈现包含清晰塞音但有声语音(如元音)被噪声干扰的句子,评估了塞音对噪声环境中语音识别的贡献。结果表明,语音识别有显著(三倍)改善,尤其是在低信噪比水平(-5分贝)时。实验2评估了在一个频率区域内提供塞音频谱的部分信息,而让其余频谱区域保持不变(即被噪声干扰)的重要性。研究发现,获取清晰塞音频谱的低频(0 - 1000赫兹)区域就足以实现性能的显著提升,这归因于发声信息传递的改善。这两个实验的结果表明,性能的大部分提升必定归因于对声学标记的更好获取,声学标记在表明塞音起始的频谱不连续中很明显。这些标记在嘈杂条件下常常模糊不清,对于理解噪声中的语音以更好地确定音节结构和单词边界至关重要。

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