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Distant-talking speech recognition based on a 3-D Viterbi searchusing a microphone array

机译:使用麦克风阵列基于3-D维特比搜索的远距离语音识别

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This paper focuses on microphone arrays to realize distant-talking speech recognition in real environments. In distant-talking situations, users can speak at arbitrary positions while moving. Therefore, it,is very important for high quality speech acquisition using microphone arrays to localize a talker accurately. However, it is very difficult to localize a moving talker in noisy and reverberant environments. The talker localization errors result in performance degradation of speech recognition. One way to solve this problem is to integrate the speech recognition process and the talker localization into a unified framework. This paper proposes a new speech recognition algorithm based on a three-dimensional (3-D) Viterbi search. The 3-D Viterbi method extracts a direction-time sequence of parameter vectors by steering a beam to every direction in every frame, then finds the most likely path in a 3-D trellis space composed of talker directions, input frames and HMM states. This means that speech recognition and talker localization are performed simultaneously within a statistical framework. To evaluate the performance of the 3-D Viterbi method, recognition experiments for real environment data were carried out. The results confirmed that the 3-D Viterbi method drastically improves the recognition performance for the moving talker case as well as for the fixed-position talker case
机译:本文重点讨论了麦克风阵列,以在真实环境中实现远距离语音识别。在远距离交谈的情况下,用户可以在移动时在任意位置讲话。因此,这对于使用麦克风阵列准确定位讲话者的高质量语音获取非常重要。但是,很难在嘈杂和混响的环境中定位移动的讲话者。讲话者定位错误会导致语音识别性能下降。解决此问题的一种方法是将语音识别过程和讲话者本地化集成到一个统一的框架中。本文提出了一种新的基于三维(3-D)维特比搜索的语音识别算法。 3-D维特比方法是通过将光束转向每一帧中的每个方向来提取参数向量的方向-时间序列,然后在3-D格状空间中找到最可能的路径,该空间由发话者方向,输入帧和HMM状态组成。这意味着语音识别和讲话者本地化是在统计框架内同时执行的。为了评估3-D维特比方法的性能,对真实环境数据进行了识别实验。结果证实,3-D维特比方法极大地提高了对移动讲话者壳体和固定位置讲话者壳体的识别性能。

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