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Using longest common subsequence and character models to predict word formsстатья
- Автор: Sorokin Alexey
- Сборник: Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology
- Год издания: 2016
- Место издания: Association for Computational Linguistics (ACL)
- Первая страница: 54
- Последняя страница: 61
- DOI: 10.18653/v1/w16-2009
- Аннотация: This paper presents an algorithm for automatic word forms inflection. We use the method of longest common subsequence to extract abstract paradigms from given pairs of basic and inflected word forms, as well as suffix and prefix features to predict this paradigm automatically. We elaborate this algorithm using combination of affix feature-based and character ngram models, which substantially enhances performance especially for the languages possessing nonlocal phenomena such as vowel harmony. Our system took part in SIGMORPHON 2016 Shared Task and took 3rd place in 17 of 30 subtasks and 4th place in 7 substasks among 7 participants.
- Добавил в систему: Сорокин Алексей Андреевич