Noise robust speech parameterization using multiresolution feature extraction.

In this paper, we present a multiresolution-based feature extraction technique for speech recognition in adverse conditions. The proposed front-end algorithm uses mel cepstrum-based feature computation of subbands in order not to spread noise distortions over the entire feature space. Conventional f...

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Detaylı Bibliyografya
Yayımlandı:	IEEE Transactions on speech and audio processing 9, 8 (2001).
Yazar:	Hariharan, R.
Materyal Türü:	Makale
Dil:	English
Konular:	HMM parameters. PCA transform. SNR. Cepstral domain feature vector normalization. Computational complexity reduction. Connected digit recognition task. Feature vector dimension. Front-end algorithm. Long-term spectral information. Mel cepstrum-based feature computation. Multiresolution-based feature extraction. Noise conditions. Noise robustness. Speech parameterization. Speech recognition. Subbands full-band features. Word recognition accuracy.