Unsupervised word segmentation from discrete speech units in low-resource settings

Boito, M.Z., Yusuf, B., Ondel, L. et al. (2 more authors) (2022) Unsupervised word segmentation from discrete speech units in low-resource settings. In: Melero, M., Sakti, S. and Soria, C., (eds.) Proceedings of the LREC 2022 Workshop of the 1st Annual Meeting of the ELRA/ISCA Special Interest Group on Under-Resourced Languages (SIGUL 2022). 1st Annual Meeting of the ELRA/ISCA Special Interest Group on Under-Resourced Languages (SIGUL 2022), 24-25 Jun 2022, Marseille, France. European Language Resources Association (ELRA) , pp. 1-9. ISBN 9791095546917

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2022 European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0 (http://creativecommons.org/licenses/by-nc/4.0/).
Keywords: unsupervised word segmentation; speech discretization; acoustic unit discovery; low-resource settings
Dates:
  • Published (online): 30 June 2022
  • Published: 30 June 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
FunderGrant number
Engineering and Physical Sciences Research CouncilEP/T02450X/1
Depositing User: Symplectic Sheffield
Date Deposited: 01 Sep 2022 13:12
Last Modified: 01 Sep 2022 13:12
Published Version: https://sigul-2022.ilc.cnr.it/
Status: Published
Publisher: European Language Resources Association (ELRA)
Refereed: Yes

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