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This paper hypothesizes that transfer-based machine translation systems can be improved by encoding information structure in both the source and target grammars, and preserving information structure in the transfer stage. We explore how information structure can be represented within the HPSG/MRS formalism (Pollard and Sag, 1994; Copestake et al., 2005) and how it can help refine multilingual MT. Building upon that framework, we provide a sample translation between English and Japanese and check the feasibility of the proposals in small-scale translation systems built with the HPSG/MRS-based LOGON MT infrastructure (Oepen et al., 2007). Our experiment shows the information structure-based MT system that we propose in this paper reduces the number of translations 75.71% for Japanese and 80.23% for Korean. The dramatic reductions in the number of translations is expected to make a contribution to our HPSG/MRS-based MT in terms of latency as well as accuracy.
Der Beitrag behandelt zunächst die Frage, welche Vorteile elektronische Wörterbücher gegenüber traditionell gedruckten Wörterbüchern besitzen. Danach werden drei Online-Programme zur automatischen Übersetzung (Babelfish, Google Übersetzer, Bing Translator) vorgestellt. Beispieltexte werden mit diesen Programmen übersetzt, danach wird die jeweilige Qualität der Übersetzungen beurteilt. Schließlich diskutiert der Beitrag noch die Folgen, die durch die Möglichkeiten automatischen Übersetzens für die Auslandsgermanistik zu erwarten sind. Dabei zeigt sich, dass Programme für das automatische Übersetzen künftig durchaus ernstzunehmende Auswirkungen auf die philologischen Wissenschaften haben können.
The aim of any Automatic Translation project is to give a mechanical procedure for finding an equivalent expression in the target language to any sentence in the source language. The aim of my linguistic translation project is to find the corresponding structures of the languages dealt with. The two main problems that have to be solved by such a project are the difference of word order between the source language and the target language and the ambiguous words of the source language for which the appropriate word in the target language has to be chosen. The first problem is of major linguistic interest: once the project has been worked out, it will give us the parallel sentence structures for the two languages in question. Since there is no complete analysis of any language that could be used for the purpose of automatic translation, we decided to build up our project sentence by sentence. The rules which are needed for translating each sentence will have to be included in the complete program anyway, and the translation may be checked and corrected immediately. The program is split up into subroutines for each word-class, so that a correction of the program in case of an unsatisfactory translation does not complicate the program unnecessarily.