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Usage of Frame Dropping and Frame Attenuation Algorithms in Automatic Speech Recognition Systems

机译:自动语音识别系统中帧掉落和帧衰减算法的用途

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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 that small word error rate can be achieved at small number of Gaussian mixtures if either frame dropping or frame attenuation algorithm is used.
机译:本文提出了自动语音识别系统中帧滴加和帧衰减算法的使用。一方面,使用帧掉落算法是重要的,因为语音识别系统不需要处理输入信号的噪声部分,但另一方面,如果频谱大小,则语音识别结果可以更好仅噪声帧衰减。提出了一种基于帧丢弃所需的日志滤波器库幅度的语音活动检测(VAD)的新方法,或者用所谓的“宿醉标准”帧衰减。所有测试都是在斯洛文尼亚语,德语和西班牙固定电话SpeemDAT II数据库上进行的,使用HTK语音识别工具包。获得的结果表明,如果使用帧丢弃或帧衰减算法,则可以在少量高斯混合中实现小字错误率。

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