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Efficient Wordgraph Pruning for Interactive Translation Prediction. Proceedings of the 17th Annual Conference of the European Association for Machine Translation (EAMT'14), 2014. pp. 27-34.When applying interactive translation prediction in real-life scenarios, response time is critical for the users to accept the interactive translation prediction system as a potentially useful tool. In this paper, we report on three different strategies for reducing the computation time required by a state-of-the-art interactive translation prediction system, so that automatic completions are delivered in real time. The best possibility turns out to be to directly prune the wordgraphs derived from the search procedure, achieving real-time response rates without any degradation whatsoever in the quality of the completions provided.