Abstract
We present a novel cross-lingual transfer method for paradigm completion, the task of mapping a lemma to its inflected forms, using a neural encoder-decoder model, the state of the art for the monolingual task. We use labeled data from a high-resource language to increase performance on a low-resource language. In experiments on 21 language pairs from four different language families, we obtain up to 58% higher accuracy than without transfer and show that even zero-shot and one-shot learning are possible. We further find that the degree of language relatedness strongly influences the ability to transfer morphological knowledge.- Anthology ID:
- P17-1182
- Volume:
- Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- July
- Year:
- 2017
- Address:
- Vancouver, Canada
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1993–2003
- Language:
- URL:
- https://aclanthology.org/P17-1182
- DOI:
- 10.18653/v1/P17-1182
- Cite (ACL):
- Katharina Kann, Ryan Cotterell, and Hinrich Schütze. 2017. One-Shot Neural Cross-Lingual Transfer for Paradigm Completion. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1993–2003, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- One-Shot Neural Cross-Lingual Transfer for Paradigm Completion (Kann et al., ACL 2017)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/P17-1182.pdf