TransAhead: A Computer-Assisted Translation and Writing Tool

نویسندگان

  • Chung-Chi Huang
  • Ping-Che Yang
  • Keh-Jiann Chen
  • Jason S. Chang
چکیده

We introduce a method for learning to predict text completion given a source text and partial translation. In our approach, predictions are offered aimed at alleviating users’ burden on lexical and grammar choices, and improving productivity. The method involves learning syntax-based phraseology and translation equivalents. At run-time, the source and its translation prefix are sliced into ngrams to generate and rank completion candidates, which are then displayed to users. We present a prototype writing assistant, TransAhead, that applies the method to computer-assisted translation and language learning. The preliminary results show that the method has great potentials in CAT and CALL with significant improvement in translation quality across users.

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تاریخ انتشار 2012