An efficient Voice Activity Detection method for Automatic Tamil Speech Recognition System using VADSOHN algorithm

V. Radha, C. Vimala, M. Krishnaveni
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引用次数: 4

Abstract

In the emerging trend of speech technologies, speech/non-speech detection is an unsolved problem, which affects numerous speech related applications. Especially in robust speech recognition, there is always a need for a noise reduction scheme working in combination with a precise Voice Activity Detector (VAD). The approach in this paper is based on filtering Tamil speech signal, which is fed as an input to avoid high-energy noisy component and then to determine the speech/non speech in a given signal. Henceforth this research proposes an improved VAD for Automatic Tamil Speech Recognition System (ATSRS). Four types of Infinite Impulse Response (IIR) filters and three VAD techniques are used for the above-mentioned work. These techniques are compared and the best combination of filter with VAD is proposed for ATSRS. By experimental results the proposed method, which is the combination of elliptic Filter with VAD based on sohn's method, which gives better results more effectively. The performance evaluation is done with the speech quality measures like MSE and PSNR.
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基于VADSOHN算法的泰米尔语自动语音识别系统中有效的语音活动检测方法
在语音技术的新兴趋势中,语音/非语音检测是一个尚未解决的问题,它影响了许多语音相关的应用。特别是在鲁棒语音识别中,总是需要一种与精确的语音活动检测器(VAD)相结合的降噪方案。本文的方法是在对泰米尔语信号进行滤波的基础上,将泰米尔语信号作为输入,避免高能量的噪声成分,进而确定给定信号中的语音/非语音。因此,本研究提出一种改进的泰米尔语自动语音识别系统(ATSRS)的VAD。四种类型的无限脉冲响应(IIR)滤波器和三种VAD技术用于上述工作。对这些技术进行了比较,提出了用于ATSRS的滤波器与VAD的最佳组合。实验结果表明,在sohn方法的基础上,将椭圆滤波器与VAD相结合,能更有效地获得较好的滤波效果。性能评估是用MSE和PSNR等语音质量指标来完成的。
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