One-Shot Neural Cross-Lingual Transfer for Paradigm Completion
March 31, 2017 ยท Declared Dead ยท ๐ Annual Meeting of the Association for Computational Linguistics
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Authors
Katharina Kann, Ryan Cotterell, Hinrich Schรผtze
arXiv ID
1704.00052
Category
cs.CL: Computation & Language
Citations
40
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
6 months ago
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.
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