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This paper presents a novel feature extractor for robust large vocabulary continuous speech recognition (LVCSR) task. For accurate and robust estimation of speech power spectrum we propose to compute the features from the regularized minimum variance distortionless response (regMVDR) spectral estimate instead of the windowed periodogram estimate. A sigmoid shape subband spectrum enhancement technique...
This paper presents regularized minimum variance distortion-less response (MVDR)-based cepstral features for robust continuous speech recognition. The mel-frequency cepstral coefficient (MFCC) features, widely used in speech recognition tasks, are usually computed from a direct spectrum estimate, that is, the squared magnitude of the discrete Fourier transform (DFT) of speech frames. Direct spectrum...
This paper presents asymmetric taper (or window)-based robust Mel frequency cepstral coefficient (MFCC) feature extraction for automatic speech recognition (ASR). Commonly, MFCC features are computed from a symmetric Hamming-tapered direct-spectrum estimate. Symmetric tapers have linear phase and also imply longer time delay. In ASR systems, phase information is usually discarded as human speech perception...
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