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In this paper, a novel hybrid feature extraction algorithm is proposed, which implements forward masking, lateral inhibition, and temporal integration with a simple 2D psychoacoustic filter. The proposed algorithm consists of two key parts, the 2D psychoacoustic filter and cepstral mean variance normalization (CMVN). Mathematical derivation is provided to show the correctness of the 2D psychoacoustic...
Human auditory system performs better than speech recognition system under noisy condition, which leads us to the idea of incorporating the human auditory system into automatic speech recognition engines. In this paper, a hybrid feature extraction method, which utilizes forward masking, backward masking, and lateral inhibition, is incorporated into mel-frequency cepstral coefficients (MFCC). The integration...
One of the weaknesses of speech recognition system is its lack of robustness to background noise as compared to human listeners under similarly conditions. This paper proposes a 2D psychoacoustic modeling algorithm which is integrated with a feature extraction front-end for hidden Markov model (HMM). The proposed algorithm incorporates the properties of human auditory system and applies it to the...
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