Assisting Translators in Indirect Lexical Transfer

Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pages 136–143, Prague, Czech Republic, June 2007. c⃝2007 Association for Computational Linguistics Assisting Translators in Indirect Lexical Transfer Bogdan Babych, Anthony Hartley, Serge Sharoff Centre for Translation Studies University of Leeds, UK {b.babych,a.hartley,s.sharoff}@leeds.ac.uk Olga Mudraya Department of Linguistics Lancaster University, UK o.mudraya@lancs.ac.uk Abstract We present the design and evaluation of a translator’s amenuensis that uses compa- rable corpora to propose and rank non- literal solutions to the translation of expres- sions from the general lexicon. Using dis- tributional similarity and bilingual diction- aries, the method outperforms established techniques for extracting translation equivalents from parallel corpora. The in- terface to the system is available at: http://corpus.leeds.ac.uk/assist/v05/ 1 Introduction This paper describes a system designed to assist humans in translating expressions that do not nec- essarily have a literal or compositional equivalent in the target language (TL). In the spirit of (Kay, 1997), it is intended as a translator's amenuensis "under the tight control of a human translator … to help increase his productivity and not to supplant him". One area where human translators particularly appreciate assistance is in the translation of expres- sions from the general lexicon. Unlike equivalent technical terms, which generally share the same part-of-speech (POS) across languages and are in the ideal case univocal, the contextually appropri- ate equivalents of general language expressions are often indirect and open to variation. While the transfer module in RBMT may acceptably under- generate through a many-to-one mapping between source and target expressions, human translators, even in non-literary fields, value legitimate varia- tion. Thus the French expression il faillit échouer (lit.: he faltered to fail) may be variously rendered as he almost/nearly/all but failed; he was on the verge/brink of failing/failure; failure loomed. All of these translations are indirect in that they in- volve lexical shifts or POS transformations. Finding such translations is a hard task that can benefit from automated assistance. 'Mining' such indirect equivalents is difficult, precisely because of the structural mismatch, but also because of the paucity of suitable aligned corpora. The approach adopted here includes the use of comparable cor- pora in source and target languages, which are relatively easy to create. The challenge is to gener- ate a list of usable solutions and to rank them such that the best are at the top. Thus the present system is unlike SMT (Och and Ney, 2003), where lexical selection is effected by a translation model based on aligned, parallel cor- pora, but the novel techniques it has developed are exploitable in the SMT paradigm. It also differs from now traditional uses of comparable corpora for detecting translation equivalents (Rapp, 1999) or extracting terminology (Grefenstette, 2002), which allows a one-to-one correspondence irre- spective of the context. Our system addresses diffi- culties in expressions in the general lexicon, whose translation is context-dependent. The structure of the paper is as follows. In Sec- tion 2 we present the method we use for mining translation equivalents. In Section 3 we …

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