Abstract

We propose the energy-constrained minimum-variance response (ECMVR) filter to perform robust spectral estimation of vowels. We modify the distortionless constraint of the minimum-variance distortionless response (MVDR) filter and add an energy constraint to its formulation to mitigate the influence of noise on the speech spectrum. We test our ECMVR filter on a vowel classification task with different background noises at various SNR levels. Results show that vowels are classified more accurately in certain noises using MFCC and PLP features extracted from the ECMVR spectrum compared to using features extracted from the FFT and MVDR spectra.

Date

2014

Authors

Colin Vaz, Andreas Tsiartas, Shrikanth Narayanan

Conference

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Pages

6275-6279

Publisher

IEEE