Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/90388
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Title: Automatic learning of modality exclusivity norms with crosslingual word embeddings
Authors: Chersoni, E 
Xiang, R 
Lu, Q 
Huang, CR 
Issue Date: Dec-2020
Source: Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics, Barcelona, Spain, December 2020, p. 32-38
Abstract: Collecting modality exclusivity norms for lexical items has recently become a common practice in psycholinguistics and cognitive research. However, these norms are available only for a relatively small number of languages and often involve a costly and time-consuming collection of ratings.
In this work, we aim at learning a mapping between word embeddings and modality norms. Our experiments focused on crosslingual word embeddings, in order to predict modality association scores by training on a high-resource language and testing on a low-resource one. We ran two experiments, one in a monolingual and the other one in a crosslingual setting. Results show that modality prediction using off-the-shelf crosslingual embeddings indeed has moderate-to-high correlations with human ratings even when regression algorithms are trained on an English resource and tested on a completely unseen language.
Rights: © 1963–2021 ACL
This work is licensed under a Creative Commons Attribution 4.0 International License. License details: http://creativecommons.org/licenses/by/4.0/.
The following publication Chersoni, E., Xiang, R., Lu, Q., & Huang, C. R. (2020, December). Automatic learning of modality exclusivity norms with crosslingual word embeddings. In Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics (pp. 32-38) is available at https://www.aclweb.org/anthology/2020.starsem-1.4
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