Are All Good Word Vector Spaces Isomorphic?
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Documents
- Are All Good Word Vector Spaces Isomorphic
Final published version, 637 KB, PDF document
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”).
Original language | English |
---|---|
Title of host publication | Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) |
Publisher | Association for Computational Linguistics |
Publication date | 2020 |
Pages | 3178–3192 |
DOIs | |
Publication status | Published - 2020 |
Event | The 2020 Conference on Empirical Methods in Natural Language Processing - online Duration: 16 Nov 2020 → 20 Nov 2020 http://2020.emnlp.org |
Conference
Conference | The 2020 Conference on Empirical Methods in Natural Language Processing |
---|---|
Location | online |
Periode | 16/11/2020 → 20/11/2020 |
Internetadresse |
ID: 258388356