From Synsets to Videos: Enriching ItalWordNet Multimodally.

LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION(2014)

引用 23|浏览29
暂无评分
摘要
The paper describes the multimodal enrichment of ItalWordNet action verbs' entries by means of an automatic mapping with a conceptual ontology of action types instantiated by video scenes (ImagAct). The two resources present significative differences as well as interesting complementary features, such that a mapping of these two resources can lead to a an enrichment of IWN, through the connection between synsets and videos apt to illustrate the meaning described by glosses. Here, we describe an approach inspired by ontology matching methods for the automatic mapping of ImagAct video scenes onto ItalWordNet. The experiments described in the paper are conducted on Italian, but the same methodology can be extended to other languages for which WordNets have been created, since ImagAct is available also for English, Chinese and Spanish. This source of multimodal information can be exploited to design second language learning tools, as well as for language grounding in action recognition in video sources and potentially for robotics.
更多
查看译文
关键词
action ontology,multimodality,WordNet
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要