Abstract
Speech recognition rate drops significantly when interfered by noise in complex environment. In order to improve the accuracy and the robustness of the speech recognition in adverse acoustical environments, this paper reviewed the main problems of noise robust speech recognition, proposed a multi-space compensation algorithm which from signal-space, feature-space and model-space based on wiener filter, histogram equalization and vector Taylor series. Theory analyses and experiment results show that the proposed method can overcome the defect of the sharp descent of speech recognition rate of existing speech recognition algorithm interfered by environmental noise and improve the accuracy and the robustness in adverse acoustical environments. The algorithm provides the theoretical support for the speech recognition in airport, station, wharf and other complex noise environment.
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