The SIGTYP 2022 Shared Task on the Prediction of Cognate Reflexes

Johann-Mattis List, Ekaterina Vylomova, Robert Forkel, Nathan Hill, Ryan Cotterell


Abstract
This study describes the structure and the results of the SIGTYP 2022 shared task on the prediction of cognate reflexes from multilingual wordlists. We asked participants to submit systems that would predict words in individual languages with the help of cognate words from related languages. Training and surprise data were based on standardized multilingual wordlists from several language families. Four teams submitted a total of eight systems, including both neural and non-neural systems, as well as systems adjusted to the task and systems using more general settings. While all systems showed a rather promising performance, reflecting the overwhelming regularity of sound change, the best performance throughout was achieved by a system based on convolutional networks originally designed for image restoration.
Anthology ID:
2022.sigtyp-1.7
Volume:
Proceedings of the 4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP
Month:
July
Year:
2022
Address:
Seattle, Washington
Venues:
NAACL | SIGTYP
SIG:
SIGTYP
Publisher:
Association for Computational Linguistics
Note:
Pages:
52–62
Language:
URL:
https://aclanthology.org/2022.sigtyp-1.7
DOI:
10.18653/v1/2022.sigtyp-1.7
Bibkey:
Cite (ACL):
Johann-Mattis List, Ekaterina Vylomova, Robert Forkel, Nathan Hill, and Ryan Cotterell. 2022. The SIGTYP 2022 Shared Task on the Prediction of Cognate Reflexes. In Proceedings of the 4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP, pages 52–62, Seattle, Washington. Association for Computational Linguistics.
Cite (Informal):
The SIGTYP 2022 Shared Task on the Prediction of Cognate Reflexes (List et al., SIGTYP 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.sigtyp-1.7.pdf