Are All Good Word Vector Spaces Isomorphic?
Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)
Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)
Association for Computational Linguistics
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Vulic, I., Ruder, S., & Søgaard, A. (2020). Are All Good Word Vector Spaces Isomorphic?. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020) https://doi.org/10.18653/v1/2020.emnlp-main.257
Existing algorithms for aligning cross-lingual word vector spaces assume that vector spaces are approximately isomorphic. As a result, they perform poorly or fail completely on non-isomorphic spaces. Such non-isomorphism has been hypothesised to result from typological differences between languages. In this work, we ask whether non-isomorphism is also crucially a sign of degenerate word vector spaces. We present a series of experiments across diverse languages which show that variance in performance across language pairs is not only due to typological differences, but can mostly be attributed to the size of the monolingual resources available, and to the properties and duration of monolingual training (e.g. "under-training").
ECH2020 EUROPEAN RESEARCH COUNCIL (ERC) (648909)
External DOI: https://doi.org/10.18653/v1/2020.emnlp-main.257
This record's URL: https://www.repository.cam.ac.uk/handle/1810/315100
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