Reverberant speech recognition: A phoneme analysis

Pablo Peso Parada, D. Sharma, P. Naylor, T. Waterschoot
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引用次数: 8

Abstract

We present a phoneme confusion analysis that models the impact of reverberation on automatic speech recognition performance by formulating the problem in a Bayesian framework. Our analysis under reverberant conditions shows the relative robustness to reverberation of each phoneme and also indicates that substitutions and deletions correspond to the most common errors in a phoneme recognition task. Finally, a model is proposed to estimate the confusability of each phoneme depending on the reverberation level which is evaluated using two independent data sets.
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混响语音识别:音素分析
我们提出了一个音素混淆分析,通过在贝叶斯框架中制定问题,模拟混响对自动语音识别性能的影响。我们在混响条件下的分析显示了每个音素对混响的相对鲁棒性,并且还表明替换和删除对应于音素识别任务中最常见的错误。最后,提出了一个模型来估计每个音素的混淆性取决于混响水平,该模型使用两个独立的数据集进行评估。
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