Cross-lingual Visual Verb Sense Disambiguation
University of Edinburgh（爱丁堡大学）；University of Copenhagen（哥本哈根大学）
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
