Publication | Closed Access
ViVo
16
Citations
21
References
2017
Year
Unknown Venue
Natural Language ProcessingMultimodal LlmEngineeringInformation RetrievalCorpus LinguisticsComputational LinguisticsNovel Video-augmented DictionaryLanguage AcquisitionVideo RetrievalVision Language ModelVideo SummarizationVideo-augmented DictionaryVideo UnderstandingLanguage StudiesLanguage LearningComputer-assisted Language LearningLinguisticsText Mining
Research on Computer-Assisted Language Learning (CALL) has shown that the use of multimedia materials such as images and videos can facilitate interpretation and memorization of new words and phrases by providing richer cues than text alone. We present ViVo, a novel video-augmented dictionary that provides an inexpensive, convenient, and scalable way to exploit huge online video resources for vocabulary learning. ViVo automatically generates short video clips from existing movies with the target word highlighted in the subtitles. In particular, we apply a word sense disambiguation algorithm to identify the appropriate movie scenes with adequate contextual information for learning. We analyze the challenges and feasibility of this approach and describe our interaction design. A user study showed that learners were able to retain nearly 30% more new words with ViVo than with a standard bilingual dictionary days after learning. They preferred our video-augmented dictionary for its benefits in memorization and enjoyable learning experience.
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