Interactive Second Language Learning from News Websites
Research Area: Natural Language Processing Year: 2015
Type of Publication: In Proceedings  
  • Tao Chen
  • Naijia Zheng
  • Yue Zhao
  • Muthu Kumar Chandrasekaran
  • Min-Yen Kan
We propose WordNews, a web browser extension that allows readers to learn a second language vocabulary while reading news online. Injected tooltips allow readers to look up selected vocabulary and take simple interactive tests. We discover that two key system components needed improvement, both which stem from the need to model context. These two issues are real-world word sense disambiguation (WSD) to aid translation quality and constructing interactive tests. For the first, we start with Microsoft’s Bing translation API but employ additional dictionary-based heuristics that significantly improve translation in both coverage and accuracy. For the second, we propose techniques for generating appropriate distractors for multiple-choice word mastery tests. Our preliminary user survey confirms the need and viability of such a language learning platform.
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