Statistical translation of text and speech: First results with the RWTH system

Christoph Tillmann, Stephan Vogel, Hermann Ney, Hassan Sawaf

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In this paper, we describe a first version of a system for statistical translation and present experimental results. The statistical translation approach uses two types of information: a translation model and a language model. The language model used is a standard bigram model. The translation model 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 a bilingual corpus is available: the EuTrans traveller task (Spanish-English, 500-word vocabulary) and the Verbmobil task (German-English, 3000-word vocabulary). 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.

Original languageEnglish
Article number257857
Pages (from-to)43-74
Number of pages32
JournalMachine Translation
Volume15
Issue number1-2
DOIs
Publication statusPublished - 1 Jan 2000

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Keywords

  • Bilingual alignment
  • Dynamic programming
  • Hidden Markov models
  • Learning from bilingual corpora
  • Statistical machine translation

ASJC Scopus subject areas

  • Software
  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence

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