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• W2061439074 abstract "State-of-the-art Machine Translation (MT) systems are still far from being perfect. An alternative is the so-called Interactive Machine Translation (IMT). In this paper, we present some novel methods to improve the statistical phrase-based IMT. We utilize dynamic distortion limitation to balance the requirements of long distance reordering and decoding speed. And we introduce the difference function to the translation hypothesis extension as a heuristic function, to make the final translation candidates as diverse as possible. We also use the user validated prefix to direct the word selection of suffix based on a word co-occurrence model. All these methods aim at optimizing the first N-best candidate translations and look forward to reducing the cognitive burden of the users. The experiential results show the effectiveness of our methods." @default.
• W2061439074 created "2016-06-24" @default.
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• W2061439074 date "2013-08-01" @default.
• W2061439074 modified "2023-09-27" @default.
• W2061439074 title "Improvements in Statistical Phrase-Based Interactive Machine Translation" @default.
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• W2061439074 doi "https://doi.org/10.1109/ialp.2013.27" @default.
• W2061439074 hasPublicationYear "2013" @default.
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