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Amplitude Modulation Filters as Feature Sets for Robust ASR: Constant Absolute or Relative Bandwidth?

机译:幅度调制滤波器作为强鲁的ASR的功能集:恒定绝对或相对带宽?

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Many research efforts in the field of feature extraction for automatic speech recognition are focused on analyzing slow amplitude fluctuations of speech. In this study the importance of spectral and temporal resolution for the amplitude modulation frequency analysis are investigated in order to provide guidance for the appropriate filter design. Therefore, different wavelet and Fourier transform like filter time scales are examined, i.e. the importance of time and frequency separation is compared. The results demonstrate that analyzing three separate amplitude modulation frequency bands of constant absolute bandwidth that cover the range from about 2 to 16 Hz are sufficient for automat-icspeech recognition.
机译:自动语音识别特征提取领域的许多研究努力集中在分析语音的慢幅度波动。在该研究中,研究了幅度调制频率分析的光谱和时间分辨率的重要性,以便为适当的过滤器设计提供指导。因此,检查了不同的小波和傅里叶变换,如滤波时间尺度,即比较时间和频率分离的重要性。结果表明,分析了三个单独的绝对带宽频带,其覆盖大约2到16Hz的范围足以实现自动机构 - ICSPeech识别。

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