Publication detail

Dereverberation and Beamforming in Far-Field Speaker Recognition

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

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/"
}

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