Analog auditory perception model for robust speech recognition

An auditory perception model for noise-robust speech feature extraction is presented. The model assumes continuous-time filtering and rectification, amenable to real-time, low-power analog VLSI implementation. A 3 mm×3 mm CMOS chip in 0.5 μm CMOS technology implements the general form of the model with digitally programmable filter parameters. Experiments on the TI-DIGIT database demonstrate consistent robustness of the new features to noise of various statistics, yielding significant improvements in digit recognition accuracy over models identically trained using Mel-scale frequency cepstral coefficient (MFCC) features.