Incorporating Codebook and Utterance Information in Cepstral Statistics Normalization Techniques for Robust Speech Recognition in Additive Noise Environments

[[abstract]]Cepstral statistics normalization techniques have been shown to be very successful at improving the noise robustness of speech features. This letter proposes a hybrid-based scheme to achieve a more accurate estimate of the statistical information of features in these techniques. By properly integrating codebook and utterance knowledge, the resulting hybrid-based approach significantly outperforms conventional utterance-based, segment-based and codebook-based approaches in additive noise environments. Furthermore, the high-performance CS-HEQ can be implemented with a short delay and can thus be applied in real-time online systems.[[note]]SC