Bidirectional OM-LSA speech estimator for noise robust speech recognition

Y. Obuchi, Ryu Takeda, M. Togami
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引用次数: 6

Abstract

A new speech enhancement method using bidirectional speech estimator is introduced. A widely-known speech enhancement method using the optimally-modified log spectral amplitude (OM-LSA) speech estimator is re-modified under the assumption that the frame-synchronous estimation is not essential in some of the speech recognition applications. The new method utilizes two separate flows of the speech gain estimation, one is along the forward direction of time and the other along the backward direction. A simple look-ahead estimation mechanism is also implemented in each flow. By taking the average of these two gains, the speech estimation becomes more robust under various noise conditions. Evaluation experiments using the artificial and real noisy speech data confirm that the speech recognition accuracy can be greatly improved by the proposed method.
用于噪声鲁棒语音识别的双向OM-LSA语音估计器
介绍了一种新的基于双向语音估计器的语音增强方法。在假设帧同步估计在某些语音识别应用中不需要的情况下,对一种广泛使用的最优修正对数谱幅(OM-LSA)语音估计器的语音增强方法进行了重新改进。该方法利用了两个独立的语音增益估计流程,一个是沿着时间的前向,另一个是沿着时间的后向。在每个流中还实现了一个简单的预检估计机制。通过取这两个增益的平均值,语音估计在各种噪声条件下都具有更强的鲁棒性。利用人工噪声和真实噪声语音数据进行的评价实验表明,该方法可以大大提高语音识别的准确率。
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