@inproceedings{chernyak-etal-2019-char,
title = "Char-{RNN} for Word Stress Detection in {E}ast {S}lavic Languages",
author = "Chernyak, Ekaterina and
Ponomareva, Maria and
Milintsevich, Kirill",
booktitle = "Proceedings of the Sixth Workshop on {NLP} for Similar Languages, Varieties and Dialects",
month = jun,
year = "2019",
address = "Ann Arbor, Michigan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-1404",
doi = "10.18653/v1/W19-1404",
pages = "35--41",
abstract = "We explore how well a sequence labeling approach, namely, recurrent neural network, is suited for the task of resource-poor and POS tagging free word stress detection in the Russian, Ukranian, Belarusian languages. We present new datasets, annotated with the word stress, for the three languages and compare several RNN models trained on three languages and explore possible applications of the transfer learning for the task. We show that it is possible to train a model in a cross-lingual setting and that using additional languages improves the quality of the results.",
}
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%0 Conference Proceedings
%T Char-RNN for Word Stress Detection in East Slavic Languages
%A Chernyak, Ekaterina
%A Ponomareva, Maria
%A Milintsevich, Kirill
%S Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects
%D 2019
%8 jun
%I Association for Computational Linguistics
%C Ann Arbor, Michigan
%F chernyak-etal-2019-char
%X We explore how well a sequence labeling approach, namely, recurrent neural network, is suited for the task of resource-poor and POS tagging free word stress detection in the Russian, Ukranian, Belarusian languages. We present new datasets, annotated with the word stress, for the three languages and compare several RNN models trained on three languages and explore possible applications of the transfer learning for the task. We show that it is possible to train a model in a cross-lingual setting and that using additional languages improves the quality of the results.
%R 10.18653/v1/W19-1404
%U https://aclanthology.org/W19-1404
%U https://doi.org/10.18653/v1/W19-1404
%P 35-41
Markdown (Informal)
[Char-RNN for Word Stress Detection in East Slavic Languages](https://aclanthology.org/W19-1404) (Chernyak et al., 2019)
ACL
- Ekaterina Chernyak, Maria Ponomareva, and Kirill Milintsevich. 2019. Char-RNN for Word Stress Detection in East Slavic Languages. In Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects, pages 35–41, Ann Arbor, Michigan. Association for Computational Linguistics.