Publication detail

The Zero Resource Speech Challenge 2020: Discovering discrete subword and word units

DUNBAR, E. KARADAYI, J. BERNARD, M. CAO, X. ALGAYRES, R. ONDEL YANG, L. BESACIER, L. SAKTI, S. DUPOUX, E.

Original Title

The Zero Resource Speech Challenge 2020: Discovering discrete subword and word units

Type

conference paper

Language

English

Original Abstract

We present the Zero Resource Speech Challenge 2020, which aims at learning speech representations from raw audio signals without any labels. It combines the data sets and metrics from two previous benchmarks (2017 and 2019) and features two tasks which tap into two levels of speech representation. The first task is to discover low bit-rate subword representations that optimize the quality of speech synthesis; the second one is to discover word-like units from unsegmented raw speech. We present the results of the twenty submitted models and discuss the implications of the main findings for unsupervised speech learning.

Keywords

zero resource speech technology, speech synthesis, acoustic unit discovery, spoken term discovery, unsupervised learning

Authors

DUNBAR, E.; KARADAYI, J.; BERNARD, M.; CAO, X.; ALGAYRES, R.; ONDEL YANG, L.; BESACIER, L.; SAKTI, S.; DUPOUX, E.

Released

25. 10. 2020

Publisher

International Speech Communication Association

Location

Shanghai

ISBN

1990-9772

Periodical

Proceedings of Interspeech

Year of study

2020

Number

10

State

French Republic

Pages from

4831

Pages to

4835

Pages count

5

URL

BibTex

@inproceedings{BUT168147,
  author="DUNBAR, E. and KARADAYI, J. and BERNARD, M. and CAO, X. and ALGAYRES, R. and ONDEL YANG, L. and BESACIER, L. and SAKTI, S. and DUPOUX, E.",
  title="The Zero Resource Speech Challenge 2020: Discovering discrete subword and word units",
  booktitle="Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",
  year="2020",
  journal="Proceedings of Interspeech",
  volume="2020",
  number="10",
  pages="4831--4835",
  publisher="International Speech Communication Association",
  address="Shanghai",
  doi="10.21437/Interspeech.2020-2743",
  issn="1990-9772",
  url="https://www.isca-speech.org/archive/Interspeech_2020/pdfs/2743.pdf"
}