Kalman filter with linear predictor and harmonic noise models for noisy speech enhancement

Yan, Qin, Vaseghi, Saeed V., Zavarehei, Esfandiar and Milner, Ben P. (2006) Kalman filter with linear predictor and harmonic noise models for noisy speech enhancement. In: 14th European Signal Processing Conference (EUSIPCO 2006), 2006-09-04 - 2006-09-08.

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Abstract

This paper presents a method for noisy speech enhancement based on integration of a formant-tracking linear prediction (FTLP) model of spectral envelope and a harmonic noise model (HNM) of the excitation of speech. The time-varying trajectories of the parameters of the LP and HNM models are tracked with Viterbi classifiers and smoothed with Kalman filters. A frequency domain pitch estimation is proposed, that searches for the peak SNRs at the harmonics. The LP-HNM model is used to deconstruct noisy speech, de-noise its LP and HNM models and then reconstitute cleaned speech. Experimental evaluations show the performance gains resulting from the formant tracking, harmonic extraction and noise reduction stages.

Item Type: Conference or Workshop Item (Paper)
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: Vishal Gautam
Date Deposited: 18 Jul 2011 12:54
Last Modified: 22 Apr 2020 09:07
URI: https://ueaeprints.uea.ac.uk/id/eprint/23435
DOI:

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