DocumentCode
179863
Title
Energy-constrained minimum variance response filter for robust vowel spectral estimation
Author
Vaz, C. ; Tsiartas, Andreas ; Narayanan, Shrikanth
Author_Institution
Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
fYear
2014
fDate
4-9 May 2014
Firstpage
6275
Lastpage
6279
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.
Keywords
FIR filters; Fourier transform spectra; acoustic noise; fast Fourier transforms; feature extraction; filtering theory; prediction theory; signal classification; speech processing; ECMVR filter; ECMVR spectrum; FFT spectra; MFCC; MVDR filter; MVDR spectra; PLP features; SNR levels; background noises; distortionless constraint; energy-constrained minimum variance response filter; minimum-variance distortionless response filter; perceptual linear prediction; speech spectrum; vowel classification task; vowel spectral estimation; Accuracy; Estimation; Feature extraction; Mel frequency cepstral coefficient; Noise; Noise measurement; Speech; MVDR; frequency estimation; robust signal processing; spectral estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6854811
Filename
6854811
Link To Document