Usage of frame dropping and frame attenuation algorithms in automatic speech recognition systems

D. Vlaj, B. Kotnik, Z. Kaciv, B. Horvat
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引用次数: 2

Abstract

In this paper the usage of frame dropping and frame attenuation algorithms in automatic speech recognition systems is presented. On the one hand, the use of frame dropping algorithms is important because the speech recognition system does not need to deal with noise-only parts of input signal, but on the other hand, the speech recognition results can be better if the spectral magnitudes of noise-only frames are attenuated. A novel approach of voice activity detection (VAD) based on the log filter-bank magnitudes needed for the frame dropping or the frame attenuation with the so-called "hangover" criterion is proposed. All tests were made on Slovenian, German, and Spanish fixed telephone SpeechDat II databases with the HTK speech recognition toolkit. The results obtained show the small word error rate can be achieved at small number of Gaussian mixtures if either frame dropping or frame attenuation algorithm is used.
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自动语音识别系统中丢帧和衰减算法的应用
本文介绍了丢帧和衰减算法在自动语音识别系统中的应用。一方面,降帧算法的使用很重要,因为语音识别系统不需要处理输入信号中只有噪声的部分,另一方面,如果对只有噪声的帧的频谱幅度进行衰减,语音识别效果会更好。提出了一种新的语音活动检测方法,该方法基于基于“宿醉”准则的帧下降或帧衰减所需的日志滤波器组幅值。所有的测试都是在斯洛文尼亚语、德语和西班牙语固定电话语音数据库中使用HTK语音识别工具包进行的。结果表明,在少量高斯混合情况下,采用降帧或衰减算法均可获得较小的字错误率。
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