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Research of Robust Feature for Speech Recognition

Feature extraction plays an important role in speech recognition. In this paper, we propose a speech feature extraction scheme which focuses on increasing the robustness of speech recognizer in noise (additive) and channel (convolutive) distortion environment. Considering the two distortions are additive in spectral and log-spectral domain, respectively, we remove the additive components by computing the time derivatives of speech frames firstly in spectral domain and then in log-spectral domain. Compared with conventional methods, this method does not need spectrum estimation and prior knowledge of noise. Experimental results confirm that our proposed method can improve the speech recognition performance in environ-ments existing both noise and channel distortions.