Detail publikace

BUT System Description to VoxCeleb Speaker Recognition Challenge 2019

ZEINALI, H. WANG, S. SILNOVA, A. MATĚJKA, P. PLCHOT, O.

Originální název

BUT System Description to VoxCeleb Speaker Recognition Challenge 2019

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

In this report, we describe the submission of Brno Universityof Technology (BUT) team to the VoxCeleb Speaker RecognitionChallenge (VoxSRC) 2019. We also provide a brief analysisof different systems on VoxCeleb-1 test sets. Submittedsystems for both Fixed and Open conditions are a fusion of4 Convolutional Neural Network (CNN) topologies. The firstand second networks have ResNet34 topology and use twodimensionalCNNs. The last two networks are one-dimensionalCNN and are based on the x-vector extraction topology. Someof the networks are fine-tuned using additive margin angularsoftmax. Kaldi FBanks and Kaldi PLPs were used as features.The difference between Fixed and Open systems lies in the usedtraining data and fusion strategy. The best systems for Fixedand Open conditions achieved 1.42 % and 1.26 % ERR on thechallenge evaluation set respectively.

Klíčová slova

VoxCeleb Speaker Recognition Challenge, Deep NeuralNetworks, ResNet, x-vector, PLDA, Cosine distance

Autoři

ZEINALI, H.; WANG, S.; SILNOVA, A.; MATĚJKA, P.; PLCHOT, O.

Vydáno

14. 9. 2019

Místo

Graz

Strany od

1

Strany do

4

Strany počet

4

URL

https://arxiv.org/abs/1910.12592

BibTex

@inproceedings{BUT168476,
  author="Hossein {Zeinali} and Shuai {Wang} and Anna {Silnova} and Pavel {Matějka} and Oldřich {Plchot}",
  title="BUT System Description to VoxCeleb Speaker Recognition Challenge 2019",
  booktitle="Proceedings of The VoxCeleb Challange Workshop 2019",
  year="2019",
  pages="1--4",
  address="Graz",
  url="https://arxiv.org/abs/1910.12592"
}

Dokumenty

zeinali_Voxceleb_2019_Interspeech_Challenge_1_.pdf