Robust speech recognition for similar pronunciation phrases using MMSE under noise environments

Masumi Watanabe, Hiroshi Tsutsui, Y. Miyanaga
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引用次数: 2

Abstract

In this paper, we propose a robust speech recognition method for similar pronunciation phrases. Along with the popularization of information devices such as personal computers and smart-phones, many applications controlled by voice have spread in the society. In order to increase the speech accuracy under a real environment, it is extremely important to discriminate similar pronunciation phrases. In the proposed method, linear prediction theory (LPC) is used for spectral analysis while cepstrum mean subtraction (CMS) and dynamic range adjustment (DRA) is used for a noise reduction method. The speech accuracy was recorded 68.7 % in SNR 10 dB by using the proposed methods. In conclusion, LPC+CMS/DRA is the most effective method to discriminate similar pronunciation phrases.
噪声环境下基于MMSE的相似发音短语鲁棒语音识别
在本文中,我们提出了一种针对相似发音短语的鲁棒语音识别方法。随着个人电脑、智能手机等信息设备的普及,社会上出现了许多语音控制的应用。为了提高真实环境下的语音准确率,对发音相近的短语进行识别是非常重要的。该方法采用线性预测理论(LPC)进行频谱分析,采用倒谱均值减法(CMS)和动态范围调整(DRA)进行降噪。在信噪比为10 dB的情况下,语音准确率达到68.7%。综上所述,LPC+CMS/DRA是识别相似发音短语最有效的方法。
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