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

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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, 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
UEA Research Groups:	Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Data Science and AI
Related URLs:	http://www.eurasip.org/Proceedings/Eusip...
Depositing User:	Vishal Gautam
Date Deposited:	18 Jul 2011 12:54
Last Modified:	10 Dec 2024 01:14
URI:	https://ueaeprints.uea.ac.uk/id/eprint/23435
DOI:

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