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- W2894916626 abstract "We develop a semantic parser which is trained in agrounded setting using pairs of videos captioned with sentences.This setting is both data-efficient requiring little annotation andfar more similar to the experience of children where they observetheir environment and listen to speakers. The semantic parserrecovers the meaning of English sentences despite not having accessto any annotated sentences and despite the ambiguity inherent invision where a sentence may refer to any combination of objects,object properties, relations or actions taken by any agent in avideo. We introduce a new corpus for grounded language acquisition.Learning to understand language, turn sentences into logical forms,by using captioned video will significantly expand the range ofdata that parsers can be trained on, lower the effort of training asemantic parser, and ultimately lead to a better understanding ofchild language acquisition." @default.
- W2894916626 created "2018-10-12" @default.
- W2894916626 creator A5082026462 @default.
- W2894916626 date "2018-01-01" @default.
- W2894916626 modified "2023-09-26" @default.
- W2894916626 title "Grounded semantic parsing using captioned videos" @default.
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