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Speech Recognition Performance as Measure of Speech Dereverberation Quality

机译:语音识别性能作为语音去混响质量的度量

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摘要

Optimal, in the sense of automatic speech recognition (ASR) accuracy maximum, parameters of the late reverberation suppression technique have been proposed in this paper. It was shown that the value 50 ms as boundary between early reflections and late reverberation, which usually is used when problems of speech quality and intelligibility is studied, isn’t best for ASR systems, for which optimal value is 100 ms. It was shown also that, when estimating late reverberation power spectrum, an optimal value of averaging parameter should be associated with statistical speech constants such as phoneme and stationary durations. Several speech quality indicators were used, and it was found that recognition accuracy is the best indicator in the sense of ability to inform the user about reached compromise between reverberation suppression and speech distortion.
机译:在自动语音识别(ASR)精度最高的意义上,本文提出了最佳的技术,用于后期混响抑制技术。结果表明,通常在研究语音质量和清晰度问题时通常使用的50 ms作为早期反射和后期混响之间的边界,对于ASR系统而言,最佳值为100 ms并不是最佳选择。还表明,当估计后期混响功率谱时,平均参数的最佳值应与统计语音常数(例如音素和固定持续时间)相关联。使用了几种语音质量指标,发现在告知用户有关混响抑制和语音失真之间达成的折衷的能力方面,识别准确度是最好的指标。

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