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By Katherine Everitt, Christopher Lim, Oren Etzioni, Jonathan Pool, Susan Colowick and Stephen Soderl


The need for translation among the world’s thousands of natural languages makes information access and communication costly. One possible solution is lemmatic communication: A human sender encodes a message into sequences of lemmata (dictionary words), a massively multilingual lexical translation engine translates them into lemma sequences in a target language, and a human receiver interprets them to infer the sender’s intended meanings. Using a 13million-lemma, 1300-language translation engine, we conducted an experiment in lemmatic communication with Spanish- and Hungarian-speaking subjects. Translingual communication was less successful than intralingual communication, and intralingual communication was less successful when the lemma sequences were artificially randomized before the receiver saw them (simulating word-order differences among languages). In all conditions, however, meanings were transmitted with high or moderate fidelity in at least 40 % of the cases. The results suggest interface and translation-algorithm improvements that could increase the efficacy of lemmatic communication.

Year: 2011
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