Publication detail

Speaker Verification with Application-Aware Beamforming

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

Original Title

Speaker Verification with Application-Aware Beamforming

Type

conference paper

Language

English

Original Abstract

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.

Keywords

Speaker verification, beamforming, xvector, generalized eigenvalue problem

Authors

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

Released

14. 12. 2019

Publisher

IEEE Signal Processing Society

Location

Sentosa, Singapore

ISBN

978-1-7281-0306-8

Book

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

Pages from

411

Pages to

418

Pages count

8

URL

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/"
}