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BLIND CHANNEL IDENTIFICATION IN SPEECH USING THE LONG-TERM AVERAGE SPEECH SPECTRUM

机译:使用长期平均语音谱盲目频道识别

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Estimation of the magnitude response of an unknown channel in single-microphone speech signals is considered. It is shown how the Long-Term Average Speech Spectrum (LTASS) can be used to identify the unknown channel and a blind channel identification algorithm is developed based on that. Furthermore, an established approximate formula for LTASS is demonstrated to be a useful tool in the context. The algorithm is evaluated using a weighted spectral distortion measure using simulated, measured and real channels with various distinct spectral characteristics. It is demonstrated that the algorithm can identify accurately the magnitude spectrum of an unknown channel in noise-free conditions. We also show results for three different additive noises where estimation accuracy is reduced but the degradation varies largely, depending on the long-term spectral characteristics of the noise.
机译:考虑了单麦克风语音信号中未知信道的幅度响应的估计。示出了如何使用长期平均语音频谱(LTAS)来识别未知信道和盲声识别算法。此外,在上下文中,证明了用于Ltass的建立的近似公式。使用具有各种不同光谱特性的模拟,测量和真实通道的加权光谱失真度量来评估该算法。证明该算法可以精确地识别无噪声条件下未知信道的幅度谱。我们还显示出三种不同的添加剂噪声的结果,其中估计精度降低,但下降差异在很大程度上,这取决于噪声的长期光谱特性。

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