A Study on Noisy Speech Recognition

K. Saeed, Adam Szczepanski
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引用次数: 3

Abstract

The paper concentrates on a speech recognition algorithm to work with speech samples of nonhomogeneous quality. The speech samples are acquired using different microphones and are of different quality. Two algorithms of feature extraction are utilized,including the use of Toeplitz matrices and distances of feature points from the Cartesian origin point (0;0) as a reference point. For classification the Nearest Neighbor approach is used. The obtained results are promising.The paper also involves the description of the process in the preparation of speech samples. The approach to estimate the frequency range which contains enough information for proper speech recognition is undertaken. The studies in this paper show that cutting frequencies above 2200 Hz have rather low influence on the proper recognition but may rather lead to increase the error rate.
噪声语音识别的研究
本文研究了一种处理非均匀语音样本的语音识别算法。语音样本是用不同的麦克风采集的,质量也不同。采用了两种特征提取算法,包括使用Toeplitz矩阵和特征点到笛卡尔原点(0;0)的距离作为参考点。对于分类,使用最近邻方法。所得结果是有希望的。本文还对语音样本的制备过程进行了描述。提出了一种估计包含足够信息的频率范围的方法。本文的研究表明,2200 Hz以上的切割频率对正确识别的影响很小,但可能导致错误率的增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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