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MOŠNER, L. MATĚJKA, P. NOVOTNÝ, O. ČERNOCKÝ, J.
Originální název
Dereverberation and Beamforming in Far-Field Speaker Recognition
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
This paper deals with far-field speaker recognition. On a corpus of NIST SRE 2010 data retransmitted in a real room with multiple microphones, we first demonstrate how room acoustics cause significant degradation of state-of-the-art ivector based speaker recognition system. We then investigate several techniques to improve the performances ranging from probabilistic linear discriminant analysis (PLDA) re-training, through dereverberation, to beamforming. We found that weighted prediction error (WPE) based dereverberation combined with generalized eigenvalue beamformer with powerspectral density (PSD) weighting masks generated by neural networks (NN) provides results approaching the clean closemicrophone setup. Further improvement was obtained by re-training PLDA or the mask-generating NNs on simulated target data. The work shows that a speaker recognition system working robustly in the far-field scenario can be developed.
Klíčová slova
Speaker recognition, microphone array, beamforming, dereverberation, audio retransmission
Autoři
MOŠNER, L.; MATĚJKA, P.; NOVOTNÝ, O.; ČERNOCKÝ, J.
Vydáno
15. 4. 2018
Nakladatel
IEEE Signal Processing Society
Místo
Calgary
ISBN
978-1-5386-4658-8
Kniha
Proceedings of ICASSP 2018
Strany od
5254
Strany do
5258
Strany počet
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/" }