LREC 2000 - Papers

LREC 2000 2^nd International Conference on Language Resources & Evaluation

Conference Papers

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Title Evaluating Translation Quality as Input to Product Development

Authors Bohan Niamh (Sail Labs GmbH, Balanstr. 57, D-81541 Munchen, nbohan@ireland.com)
Breidt Elisabeth (Sail Labs GmbH, Balanstr. 57, D-81541 Munchen, elisabeth.breidt@sail-labs.de)
Volk Martin (Department of Computer Science, University of Zurich, Winterthurerstr. 190, CH-8057 Zurich, volk@ifi.unizh.ch)

Keywords Corpora, Evaluation, Machine Translation, Rating Scales, Translation Quality

Session Session EO1 - Evaluation of Machine Translation

Abstract In this paper we present a corpus-based method to evaluate the translation quality of machine translation (MT) systems. We start with a shallow analysis of a large corpus and gradually focus the attention on the translation problems. The method constitutes an efficient way to identify the most important grammatical and lexical weaknesses of an MT system and to guide development towards improved translation quality. The evaluation described in the paper was carried out as a cooperation between an MT technology developer, Sail Labs, and the Computational Linguistics group at the University of Zurich.

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Title	Evaluating Translation Quality as Input to Product Development
Authors	Bohan Niamh (Sail Labs GmbH, Balanstr. 57, D-81541 Munchen, nbohan@ireland.com) Breidt Elisabeth (Sail Labs GmbH, Balanstr. 57, D-81541 Munchen, elisabeth.breidt@sail-labs.de) Volk Martin (Department of Computer Science, University of Zurich, Winterthurerstr. 190, CH-8057 Zurich, volk@ifi.unizh.ch)
Keywords	Corpora, Evaluation, Machine Translation, Rating Scales, Translation Quality
Session	Session EO1 - Evaluation of Machine Translation
Abstract	In this paper we present a corpus-based method to evaluate the translation quality of machine translation (MT) systems. We start with a shallow analysis of a large corpus and gradually focus the attention on the translation problems. The method constitutes an efficient way to identify the most important grammatical and lexical weaknesses of an MT system and to guide development towards improved translation quality. The evaluation described in the paper was carried out as a cooperation between an MT technology developer, Sail Labs, and the Computational Linguistics group at the University of Zurich.