Modelling function words improves unsupervised word segmentation

Mark Johnson, Anne Christophe, Emmanuel Dupoux, Katherine Demuth


Anthology ID:
P14-1027
Volume:
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
June
Year:
2014
Address:
Baltimore, Maryland
Editors:
Kristina Toutanova, Hua Wu
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
282–292
Language:
URL:
https://aclanthology.org/P14-1027
DOI:
10.3115/v1/P14-1027
Bibkey:
Cite (ACL):
Mark Johnson, Anne Christophe, Emmanuel Dupoux, and Katherine Demuth. 2014. Modelling function words improves unsupervised word segmentation. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 282–292, Baltimore, Maryland. Association for Computational Linguistics.
Cite (Informal):
Modelling function words improves unsupervised word segmentation (Johnson et al., ACL 2014)
Copy Citation:
PDF:
https://aclanthology.org/P14-1027.pdf
Video:
 https://aclanthology.org/P14-1027.mp4