Detail publikace

Speaker Verification with Application-Aware Beamforming

MOŠNER, L. PLCHOT, O. ROHDIN, J. BURGET, L. ČERNOCKÝ, J.

Originální název

Speaker Verification with Application-Aware Beamforming

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Multichannel speech processing applications usually employ beamformers as means of speech enhancement through spatial filtering. Beamformers with learnable parameters require training to minimize a loss function that is not necessarily correlated with the final objective. In this paper, we present a framework employing recent neural network based generalized eigenvalue beamformer and application-specific model that allows for optimization of beamformer w.r.t. target application. In our case, the application is speaker verification which utilizes a speaker embedding (x-vector) extractor that conveniently comes with desired loss. We show that application-specific training of the beamformer brings performance improvements over a system trained in the standard way. We perform our analysis on the recently introduced VOiCES corpus which contains multichannel data and allows us to modify the evaluation trials such that enrollment recordings remain single-channel and test utterances are multichannel.

Klíčová slova

Speaker verification, beamforming, xvector, generalized eigenvalue problem

Autoři

MOŠNER, L.; PLCHOT, O.; ROHDIN, J.; BURGET, L.; ČERNOCKÝ, J.

Vydáno

14. 12. 2019

Nakladatel

IEEE Signal Processing Society

Místo

Sentosa, Singapore

ISBN

978-1-7281-0306-8

Kniha

IEEE Automatic Speech Recognition and Understanding Workshop - Proceedings (ASRU)

Strany od

411

Strany do

418

Strany počet

8

URL

https://www.fit.vut.cz/research/publication/12152/

BibTex

@inproceedings{BUT161476,
  author="Ladislav {Mošner} and Oldřich {Plchot} and Johan Andréas {Rohdin} and Lukáš {Burget} and Jan {Černocký}",
  title="Speaker Verification with Application-Aware Beamforming",
  booktitle="IEEE Automatic Speech Recognition and Understanding Workshop - Proceedings (ASRU)",
  year="2019",
  pages="411--418",
  publisher="IEEE Signal Processing Society",
  address="Sentosa, Singapore",
  doi="10.1109/ASRU46091.2019.9003932",
  isbn="978-1-7281-0306-8",
  url="https://www.fit.vut.cz/research/publication/12152/"
}