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The performance of speech recognition systems relies on the consistency and adaptation of the speech feature in complex conditions during the training and testing stages. Traditional systems usually perform poorly under adverse noisy conditions and are not applicable to most real world problems. In this paper, we investigate the speech feature extraction problem in a noisy environment and propose...
In this paper, we investigate the speech feature extraction problem in the noisy environment. A novel approach based on Gabor filtering and tensor factorization is proposed. From recent physiological and psychoacoustic experimental results, localized spectro-temporal features are essential for auditory perception. We employ 2D-Gabor functions with different scales and directions to analyze the localized...
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