Robust speech analysis in noisy environment using running spectrum filtering

Q. Zhu, N. Ohtsuki, Y. Miyanaga, N. Yoshida
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引用次数: 11

Abstract

A new robust adaptive processing algorithm is proposed for speech parameters estimation in noisy environments; it is based on the extended least squares (ELS) method with running spectrum filtering (RSF). By utilizing RSF, we can retain speech characteristics while noise is effectively eliminated. Then, by using ELS, formants of ARMA parameters can be estimated accurately. In experiments with real speech contaminated by white Gaussian noise, it is shown that the proposed method provides robust spectrum estimation against additive noise.
基于运行频谱滤波的噪声环境下的鲁棒语音分析
针对噪声环境下语音参数估计问题,提出了一种新的鲁棒自适应处理算法。它是基于扩展最小二乘(ELS)方法和运行谱滤波(RSF)。利用RSF可以在有效消除噪声的同时保留语音特征。然后,利用ELS可以准确地估计出ARMA参数的共振峰。实验结果表明,该方法对加性噪声具有较好的鲁棒性。
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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