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Automatic Evaluation Of Machine Translation Via Word Choice And Word Order

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Abstract  We propose a novel metric ATEC for automatic MT evaluation based on explicit assessment of word choice and word order in an MT output in comparison to its reference translation(s), the two most fundamental factors in the construction of meaning for a sentence. The former is assessed by matching word forms at various linguistic levels, including surface form, stem, sound and sense, and further by weighing the informativeness of each word. The latter is quantified in term of the discordance of word position and word sequence between a translation candidate and its reference. In the evaluations using the ...
Mentions: Hong Kong City University of Hong Kong Kowloon