Publication detail

Self-supervised speaker embeddings

STAFYLAKIS, T. ROHDIN, J. PLCHOT, O. MIZERA, P. BURGET, L.

Original Title

Self-supervised speaker embeddings

Type

conference paper

Language

English

Original Abstract

Contrary to i-vectors, speaker embeddings such as x-vectors are incapable of leveraging unlabelled utterances, due to the classification loss over training speakers. In this paper, we explore an alternative training strategy to enable the use of unlabelled utterances in training. We propose to train speaker embedding extractors via reconstructing the frames of a target speech segment, given the inferred embedding of another speech segment of the same utterance. We do this by attaching to the standard speaker embedding extractor a decoder network, which we feed not merely with the speaker embedding, but also with the estimated phone sequence of the target frame sequence. The reconstruction loss can be used either as a single objective, or be combined with the standard speaker classification loss. In the latter case, it acts as a regularizer, encouraging generalizability to speakers unseen during training. In all cases, the proposed architectures are trained from scratch and in an endto- end fashion. We demonstrate the benefits from the proposed approach on the VoxCeleb and Speakers in the Wild Databases, and we report notable improvements over the baseline.

Keywords

speaker recognition, self-supervised learning, deep learning

Authors

STAFYLAKIS, T.; ROHDIN, J.; PLCHOT, O.; MIZERA, P.; BURGET, L.

Released

15. 9. 2019

Publisher

International Speech Communication Association

Location

Graz

ISBN

1990-9772

Periodical

Proceedings of Interspeech

Year of study

2019

Number

9

State

French Republic

Pages from

2863

Pages to

2867

Pages count

5

URL

BibTex

@inproceedings{BUT159999,
  author="STAFYLAKIS, T. and ROHDIN, J. and PLCHOT, O. and MIZERA, P. and BURGET, L.",
  title="Self-supervised speaker embeddings",
  booktitle="Proceedings of Interspeech",
  year="2019",
  journal="Proceedings of Interspeech",
  volume="2019",
  number="9",
  pages="2863--2867",
  publisher="International Speech Communication Association",
  address="Graz",
  doi="10.21437/Interspeech.2019-2842",
  issn="1990-9772",
  url="https://www.isca-speech.org/archive/Interspeech_2019/pdfs/2842.pdf"
}