Non-intrusive whitening of speech using Least Mean Square and divergence detection technique

Ng, Wai Pang, Elmirghani, Jaafar, Cryan, Bob and Broom, Simon (1999) Non-intrusive whitening of speech using Least Mean Square and divergence detection technique. In: GLOBECOM '99 : Global Telecommunications Conference, 5-9 December 1999, Rio de Janeireo.

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A speech whitening technique is presented and used for improved echo path modelling in telephony networks. The system identification of interest is based on the real time Least Mean Square (LMS) algorithm and a class of digital adaptive filters (DAFs). The modelling convergence rate derived from the optimal Wiener weights defines the performance criterion. A novel non-intrusive whitening technique based on the speech characteristics is exploited to whiten the speech power spectral density (PSD) whilst preserving the signal bandwidth requirements. The technique involves pre-filtering the speech using tap weight coefficients of the inverse speech spectrum. Software simulation shows an improved performance compared to the conventional LMS. A new divergence detection (DD) technique is used in a noise-impaired environment to eliminate divergence by controlling the adaptation process. The DD technique reported produces significant performance improvement in noisy environments and at echo to noise ratios (e/N) of up to 0 dB. The combined improvement reported using the whitening technique and DD is 24.5 dB after 8000 iterations (1 second) at e/N of 0 dB.

Item Type: Conference or Workshop Item (Paper)
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Becky Skoyles
Date Deposited: 16 Feb 2015 11:43
Last Modified: 12 Oct 2019 22:54

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