Machine Translation (Level 2) Anna Sågvall Hein GSLT Course, September 2004.

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Presentation transcript:

Machine Translation (Level 2) Anna Sågvall Hein GSLT Course, September 2004

Translation ”substitute the text material of one language (SL) by the equivalent text material of another language (TL)” (Catford 1965: 20) ”Translation consists in producing in the target language the closest natural equivalent of the text material of the source language, in the first hand concerning meaning, in the second hand concerning style (Nida 1975: 32) ”Translation is in theory impossible, but in practice fairly possible” Mounin (1967) Catford, J. C. (1965), A Linguistic Theory of Translation, Oxford Press, England. Mounin, G. (1967) Les problèmes théotitiques de la traduction. Paris Nida, E. (1975), A Framework for the Analysis and Evaluation of Theories of Translation, in Brislin, R. W. (ed) (1975), Translation Application and Research, Gardner Press, New York.

Equivalence form meaning style effect

Formal and dynamic equivalence Formal equivalence focuses attention on the message itself, in both form and content. It aims to allow the reader to understand as much of the SL context as possible. Dynamic equivalence is based on the principle of equivalent effect, i.e. that the relationship between receiver and message should aim at being the same as that between the original receivers and the SL message. (Nida 75)

Can computers translate? Not a simple yes or no; it depends on the purpose of the translation and the required quality.

Classical problems with MT unrealistic expectations bad translations difficulties in integrating MT in the work flow –the Ericsson case

Feasibility of machine translation quality in relation to purpose control of the source language human machine interaction re-use of translations evalution

Quality publishing quality editing quality browsing qualiy

Translation related tasks translation browsing gisting drafting message dissemination cross-language information searches cross-language interchanges

MT as a cross-language communication tool MT is used not only for pure translation purposes but also for writing in a foreign language and for browsing (Hutchins 2001) Hutchins, J., 2001, Towards a new vision for MT, Introductory speech at MT Summit VIII conference, September 2001 ( MTS-2001.pdf)

Control of the source language spell checked and grammar checked SL sublanguage –Domain –Text type controlled language

Spell checking and grammar checking If there are spelling errors or typos in the SL dictionary search will fail If there are grammatical errors in the SL grammatical analysis will fail Where and how should spell and grammar checking be accounted for? Before or in the process?

Controlled language consistent authoring of source texts –reduction of ambiguity –full linguistic coverage controlled vocabulary –full lexical coverage controlled grammar –full grammatical coverage controlled language checking –e.g. Scania Checker

Ex. of controlled languages Simplified English KANT controlled English Scania Swedish –Scania checker

Human intervention before –language checking during –e.g. ambiguity resolution after –post-editing

Re-use of translations translation memories translation dictionaries incl. terminologies lexicalistic translation statistical machine translation example-based translation

Evaluation of MT human automatic –using a gold standard coverage (recall) quality (precision) global similarity measures –merge of recall and precision –BLEU, NIST

Why machine translation? cheaper faster more consistent –when it succeeds …

What is MT proper? To be considered as MT, a system should provide minimally correct morphology minimal syntactic processing minimal semantic processing handle and produce full sentences Hutchins, J., 2000, The IAMT Certification initiative and defining translation system categories (

Examples of MT products Systran ( Comprendium (based on Metal) ProMT ( ESTeam See further: s/Compendium-4.pdf, s/Compendium-4.pdf

Basic strategies direct translation rule-based translation –transfer –interlingua example-based translation statistical translation hybrids