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 :
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