结合连接多频带和全频带概率流用于自然数语音识别

Nikki Mirghafori, N. Morgan
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引用次数: 52

摘要

多波段自动语音识别是语音识别领域中一个新兴的探索领域,近年来受到了学术界的广泛关注。研究表明,在噪声条件下,特别是在窄带噪声的情况下,多波段ASR可以减少字误差。本研究表明,在全频带(FB)信息流的基础上,在多频带(MB)信息流的基础上,采用多频带(MB)信息流,可以提高对纯净语音自然数的语音识别精度。我们还观察到类似的组合方法可以显著降低混响语音的错误率。最后,我们分析了全频带和多频带范式的误差模式,以理解为什么两种流的组合是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining connectionist multi-band and full-band probability streams for speech recognition of natural numbers
Multi-band automatic speech recognition is a new and ex-ploratory area of speech recognition which has been getting much attention in the research community. It has been shown that multi-band ASR reduces word error in noisy conditions, particularly in the case of narrow band noise. In this work we show that multi-band ASR could be used to improve the speech recognition accuracy of natural numbers for clean speech when the multi-band (MB) information stream is used in addition to the full-band (FB) one. We also observe that a similar combination method significantly reduces the error rate on reverberant speech. Finally, we analyze the error patterns of the full-band and multi-band paradigms to understand why the combination of the two streams is effective.
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