Cross-lingual Visual Verb Sense Disambiguation

Spandana Gella, Desmond Elliott, Frank Keller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent work has shown that visual context improves cross-lingual sense disambiguation for nouns. We extend this line of work to the more challenging task of cross-lingual verb sense disambiguation, introducing the MultiSense dataset of 9,504 images annotated with English, German, and Spanish verbs. Each image in MultiSense is annotated with an English verb and its translation in German or Spanish. We show that cross-lingual verb sense disambiguation models benefit from visual context, compared to unimodal baselines. We also show that the verb sense predicted by our best disambiguation model can improve the results of a  text-only machine translation system when used for a multimodal translation task.
Original languageEnglish
Title of host publicationProceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics
EditorsJill Burstein, Christy Doran, Thamar Solorio
Place of PublicationMinneapolis, Minnesota
PublisherAssociation for Computational Linguistics
Pages1998–2004
Number of pages7
Volume1
DOIs
Publication statusPublished - 7 Jun 2019
Event2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics - Minneapolis, United States
Duration: 2 Jun 20197 Jun 2019
https://naacl2019.org/

Conference

Conference2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Abbreviated titleNAACL-HLT 2019
CountryUnited States
CityMinneapolis
Period2/06/197/06/19
Internet address

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