2022
EMNLP
EMNLP 2022
Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport
Abstract
AbstractBilingual lexicons form a critical component of various natural language processing applications, including unsupervised and semisupervised machine translation and crosslingual information retrieval. In this work, we improve bilingual lexicon induction performance across 40 language pairs with a graph-matching method based on optimal transport. The method is especially strong with low amounts of supervision.
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Interdisciplinary Bridge
- Artificial Intelligence and Mathematics & Optimization and Natural Language Processing
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Hot Topic Early Bird
- low-resource language
Authors
Topics
Natural Language Processing > Applications > Information Retrieval
Natural Language Processing > Applications > Machine Translation
Natural Language Processing > Resources & Methods > Multilingual NLP
Machine Learning > Core Methods > Graphical Models
Mathematics & Optimization > Optimization > Optimal Transport
Machine Learning > Learning Types > Multi-Lingual Learning