Energy-constrained minimum variance response filter for robust vowel spectral estimation

Colin Vaz,Andreas Tsiartas,Shrikanth Narayanan

Acoustics, Speech and Signal Processing（2014）

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摘要

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.

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关键词

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,MVDR,frequency estimation,robust signal processing,spectral estimation

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