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MOŠNER, L. MATĚJKA, P. NOVOTNÝ, O. ČERNOCKÝ, J.
Original Title
Dereverberation and Beamforming in Far-Field Speaker Recognition
Type
conference paper
Language
English
Original Abstract
This paper deals with far-field speaker recognition. On a corpusof NIST SRE 2010 data retransmitted in a real roomwith multiple microphones, we first demonstrate how roomacoustics cause significant degradation of state-of-the-art ivectorbased speaker recognition system. We then investigateseveral techniques to improve the performances ranging fromprobabilistic linear discriminant analysis (PLDA) re-training,through dereverberation, to beamforming. We found thatweighted prediction error (WPE) based dereverberation combinedwith generalized eigenvalue beamformer with powerspectraldensity (PSD) weighting masks generated by neuralnetworks (NN) provides results approaching the clean closemicrophonesetup. Further improvement was obtained byre-training PLDA or the mask-generating NNs on simulatedtarget data. The work shows that a speaker recognition systemworking robustly in the far-field scenario can be developed.
Keywords
Speaker recognition, microphone array,beamforming, dereverberation, audio retransmission
Authors
MOŠNER, L.; MATĚJKA, P.; NOVOTNÝ, O.; ČERNOCKÝ, J.
Released
15. 4. 2018
Publisher
IEEE Signal Processing Society
Location
Calgary
ISBN
978-1-5386-4658-8
Book
Proceedings of ICASSP 2018
Pages from
5254
Pages to
5258
Pages count
5
URL
https://www.fit.vut.cz/research/publication/11717/
BibTex
@inproceedings{BUT155039, author="Ladislav {Mošner} and Pavel {Matějka} and Ondřej {Novotný} and Jan {Černocký}", title="Dereverberation and Beamforming in Far-Field Speaker Recognition", booktitle="Proceedings of ICASSP 2018", year="2018", pages="5254--5258", publisher="IEEE Signal Processing Society", address="Calgary", doi="10.1109/ICASSP.2018.8462365", isbn="978-1-5386-4658-8", url="https://www.fit.vut.cz/research/publication/11717/" }
Documents
mosner_icassp2018_0005254.pdf