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Statistical Translation of Text and Speech: First Results with the RWTH System
Authors:Christoph Tillimann  Stephan Vogel  Hermann Ney  Hassan Sawaf
Affiliation:(1) Lehrstuhl für Informatik VI, Rheinisch-Westfälische Technische Hochschule Aachen, Ahornstra"beta" e 55, 52056 Aachen, Germany
Abstract:In this paper, we describe a first version of a system for statisticaltranslation and present experimental results. The statistical translationapproach uses two types of information: a translation model and a languagemodel. The language model used is a standard bigram model. The translationmodel is decomposed into lexical and alignment models. After presenting the details of the alignment model, we describe the search problem and present a dynamic programming-based solution for the special case of monotone alignments.So far, the system has been tested on two limited-domain tasks for which abilingual corpus is available: the EuTrans traveller task (Spanish–English,500-word vocabulary) and the Verbmobil task (German–English, 3000-wordvocabulary). We present experimental results on these tasks. In addition to the translation of text input, we also address the problem of speech translation and suitable integration of the acoustic recognition process and the translation process.
Keywords:bilingual alignment  dynamic programming  hidden Markov models  learning from bilingual corpora  statistical machine translation
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