Perceptual MVDR-based cepstral coefficients (PMCCs) for robust speech recognition

This paper describes a robust feature extraction technique for continuous speech recognition. Central to the technique is the minimum variance distortionless response (MVDR) method of spectrum estimation. We incorporate perceptual information directly in to the spectrum estimation. This provides improved robustness and computational efficiency when compared with the previously proposed MVDR-MFCC technique. On an in-car speech recognition task this method, which we refer to as PMCC, is 15% more accurate in WER and requires approximately a factor of 4 times less computation than the MVDR-MFCC technique. On the same task PMCC yields 20% relative improvement over MFCC and 11% relative improvement over PLP frontends. Similar improvements are observed on the Aurora 2 database.