2017 ACL ACL 2017

One-Shot Neural Cross-Lingual Transfer for Paradigm Completion

Abstract

AbstractWe 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.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning and Natural Language Processing
📈 Trend Setter — Few-Shot Learning
🧭 Keyword Pioneer — paradigm completion
🐣 Hot Topic Early Bird — cross-lingual transfer
🐝 Cross-Pollinator — Artificial Intelligence, Computer Vision, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Natural Language Processing, Robotics, Speech & Audio