One-Shot Neural Cross-Lingual Transfer for Paradigm Completion

March 31, 2017 ยท Declared Dead ยท ๐Ÿ› 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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