@inproceedings{1f9edd5a936d4d9899a5854158307b60,
title = "Speaker extraction using LCMV beamformer with DNN-based SPP and RTF identification scheme",
abstract = "The linearly constrained minimum variance (LCMV)-beamformer (BF) is a viable solution for desired source extraction from a mixture of speakers in a noisy environment. The performance in terms of speech distortion, interference cancellation and noise reduction depends on the estimation of a set of parameters. This paper presents a new mechanism to update the parameters of the LCMV-BF. A new speech presence probability (SPP)-based voice activity detector (VAD) controls the noise covariance matrix update, and a speaker position identifier (SPI) procedure controls the relative transfer functions (RTFs) update. A postfilter is then applied to the BF output to further attenuate the residual noise signal. A series of experiments using real-life recordings confirm the speech enhancement capabilities of the proposed algorithm.",
author = "Ariel Malek and Chazan, {Shlomo E.} and Ilan Malka and Vladimir Tourbabin and Jacob Goldberger and Eli Tzirkel-Hancock and Sharon Gannot",
note = "Publisher Copyright: {\textcopyright} EURASIP 2017.; 25th European Signal Processing Conference, EUSIPCO 2017 ; Conference date: 28-08-2017 Through 02-09-2017",
year = "2017",
month = oct,
day = "23",
doi = "10.23919/EUSIPCO.2017.8081615",
language = "الإنجليزيّة",
series = "25th European Signal Processing Conference, EUSIPCO 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2274--2278",
booktitle = "25th European Signal Processing Conference, EUSIPCO 2017",
address = "الولايات المتّحدة",
}