Gammatone filterbank and symbiotic combination of amplitude and phase-based spectra for robust speaker verification under noisy conditions and compression artifacts

The main novelty of this work resides in incorporating a Gammatone filter-bank as a substitute of the Mel filter-bank in the extraction pipeline of the Product Spectrum PS. The proposed feature is dubbed the Gammatone Product-Spectrum Cepstral coefficients GPSCC. Experimental results are undertaken on TIMIT and noisy TIMIT corpora using the Gaussian Mixture Model with Universal Background Model (GMM-UBM) recognition algorithm. Performance evaluations indicate that GPSCC shows a drastic reduction in Equal Error Rates compared to other related features and this gain in performance is more pronounced at low signal to noise ratios. Also, our study demonstrates the merit of the Gammatone filter-bank in improving robustness to codec-degraded speech at different bit rates. Furthermore, the proposed GPSCC feature achieves the best verification performance under aggressive compression. Interestingly, at 6.60 kbps we observe that GPSCC achieves an absolute error reduction of 12% compared to the Mel Frequency Cepstral Coefficients (MFCC).