Publication detail

Analysis of DNN Speech Signal Enhancement for Robust Speaker Recognition

NOVOTNÝ, O. PLCHOT, O. GLEMBEK, O. ČERNOCKÝ, J. BURGET, L.

Original Title

Analysis of DNN Speech Signal Enhancement for Robust Speaker Recognition

Type

journal article in Web of Science

Language

English

Original Abstract

In this work, we present an analysis of a DNN-based autoencoder for speech enhancement, dereverberation and denoising. Thetarget application is a robust speaker verification (SV) system. We start our approach by carefully designing a data augmentationprocess to cover a wide range of acoustic conditions and to obtain rich training data for various components of our SV system.We augment several well-known databases used in SV with artificially noised and reverberated data and we use them to train adenoising autoencoder (mapping noisy and reverberated speech to its clean version) as well as an x-vector extractor which is cur-rently considered as state-of-the-art in SV. Later, we use the autoencoder as a preprocessing step for a text-independent SV sys-tem. We compare results achieved with autoencoder enhancement, multi-condition PLDA training and their simultaneous use.We present a detailed analysis with various conditions of NIST SRE 2010, 2016, PRISM and with re-transmitted data. We con-clude that the proposed preprocessing can significantly improve both i-vector and x-vector baselines and that this technique canbe used to build a robust SV system for various target domains.

Keywords

Speakerverification; Signalenhancement; Autoencoder; Neuralnetwork; Robustness; Embedding

Authors

NOVOTNÝ, O.; PLCHOT, O.; GLEMBEK, O.; ČERNOCKÝ, J.; BURGET, L.

Released

9. 6. 2019

ISBN

0885-2308

Periodical

COMPUTER SPEECH AND LANGUAGE

Year of study

2019

Number

58

State

United Kingdom of Great Britain and Northern Ireland

Pages from

403

Pages to

421

Pages count

19

URL

BibTex

@article{BUT158089,
  author="Ondřej {Novotný} and Oldřich {Plchot} and Ondřej {Glembek} and Jan {Černocký} and Lukáš {Burget}",
  title="Analysis of DNN Speech Signal Enhancement for Robust Speaker Recognition",
  journal="COMPUTER SPEECH AND LANGUAGE",
  year="2019",
  volume="2019",
  number="58",
  pages="403--421",
  doi="10.1016/j.csl.2019.06.004",
  issn="0885-2308",
  url="https://www.sciencedirect.com/science/article/pii/S0885230818303607"
}