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Automatic speech recognition performance in different room acoustic environments with and without dereverberation preprocessing

机译:带有和不带有混响预处理的不同房间声学环境中的自动语音识别性能

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摘要

The performance of recent dereverberation methods for reverberant speech preprocessing prior to Automatic Speech Recognition (ASR) is compared for an extensive range of room and source-receiver configurations. It is shown that room acoustic parameters such as the clarity (C50) and the definition (D50) correlate well with the ASR results. When available, such room acoustic parameters can provide insight into reverberant speech ASR performance and potential improvement via dereverberation preprocessing. It is also shown that the application of a recent dereverberation method based on perceptual modelling can be used in the above context and achieve significant Phone Recognition (PR) improvement, especially under highly reverberant conditions.
机译:针对广泛的房间和源接收器配置,比较了自动语音识别(ASR)之前用于混响语音预处理的最新混响方法的性能。结果表明,室内声学参数(如清晰度(C50)和清晰度(D50))与ASR结果具有很好的相关性。如果可用,此类室内声学参数可以通过混响预处理提供对混响语音ASR性能和潜在改进的见解。还显示出,基于感知建模的最新去混响方法的应用可以在上述上下文中使用,并且尤其在高度混响条件下,可以实现显着的电话识别(PR)改善。

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