Detail publikace

End-to-end DNN based text-independent speaker recognition for long and short utterances

ROHDIN, J. SILNOVA, A. DIEZ SÁNCHEZ, M. PLCHOT, O. MATĚJKA, P. BURGET, L. GLEMBEK, O.

Originální název

End-to-end DNN based text-independent speaker recognition for long and short utterances

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Recently several end-to-end speaker verification systems based on deep neural networks (DNNs) have been proposed. These systems have been proven to be competitive for text-dependent tasks as well as for text-independent tasks with short utterances. However, for text-independent tasks with longer utterances, end-to-end systems are still outperformed by standard i-vector + PLDA systems. In this work, we present an end-to-end speaker verification system that is initialized to mimic an i-vector + PLDA baseline. The system is then further trained in an end-to-end manner but regularized so that it does not deviate too far from the initial system. In this way we mitigate overfitting which normally limits the performance of end-to-end systems. The proposed system outperforms the i-vector + PLDA baseline on both long and short duration utterances.

Klíčová slova

Speaker verification, DNN, End-to-end, Text-independent, i-vector, PLDA

Autoři

ROHDIN, J.; SILNOVA, A.; DIEZ SÁNCHEZ, M.; PLCHOT, O.; MATĚJKA, P.; BURGET, L.; GLEMBEK, O.

Vydáno

1. 1. 2020

ISSN

0885-2308

Periodikum

COMPUTER SPEECH AND LANGUAGE

Ročník

2020

Číslo

59

Stát

Spojené království Velké Británie a Severního Irska

Strany od

22

Strany do

35

Strany počet

14

URL

https://www.sciencedirect.com/science/article/pii/S0885230818303632

BibTex

@article{BUT158088,
  author="Johan Andréas {Rohdin} and Anna {Silnova} and Mireia {Diez Sánchez} and Oldřich {Plchot} and Pavel {Matějka} and Lukáš {Burget} and Ondřej {Glembek}",
  title="End-to-end DNN based text-independent speaker recognition for long and short utterances",
  journal="COMPUTER SPEECH AND LANGUAGE",
  year="2020",
  volume="2020",
  number="59",
  pages="22--35",
  doi="10.1016/j.csl.2019.06.002",
  issn="0885-2308",
  url="https://www.sciencedirect.com/science/article/pii/S0885230818303632"
}