Title: A multichannel beamforming-based framework for speech extraction

Authors: Adel Hidri; Hamid Amiri

Addresses: Laboratoire de Recherche: Signal, Image et Technologie de l'Information (LR-SITI), École Nationale d'Ingénieurs de Tunis (ENIT), BP 37, le Belvédère, 1002 Tunis, Tunisie ' Laboratoire de Recherche: Signal, Image et Technologie de l'Information (LR-SITI), École Nationale d'Ingénieurs de Tunis (ENIT), BP 37, le Belvédère, 1002 Tunis, Tunisie

Abstract: This work proposes a new framework for multichannel speech extraction (MCSE) of one target speaker from mixtures of multiple speakers. In this framework, a beamforming technique that is based on a prior knowledge of the desired speaker's position is used. The car environment is a good example of an application where the position of the desired speaker (the driver) is known in advance. The proposed method is an optimum spatial filter with a structure inspired by the minimum variance distortionless response (MVDR) beamformer and its practical realisation through generalised side lobe canceller (GSC). The performance of the proposed method through different experiments form the 'multichannel in-car speech and noise database' must be tested and evaluated. Simulative experiments include one desired speaker (driver) and one interferer speaker (co-driver) who talked simultaneously in car environment. The experimental results show that the proposed method provides satisfactory performance.

Keywords: beamforming; microphone arrays; multichannel speech extraction; optimal filtering; multiple speakers; minimum variance distortionless response; MVDR generalised side lobe canceller; GSC; in-car speech; in-car noise; automobile industry; automotive environment.

DOI: 10.1504/IJIEI.2015.069901

International Journal of Intelligent Engineering Informatics, 2015 Vol.3 No.2/3, pp.273 - 291

Available online: 15 Jun 2015 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article