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Abstract

Juan-Carlos Amengual, José-Miguel Benedí, Francisco Casacuberta, M. Asunción Castaño, Antonio Castellanos, Víctor M. Jiménez, David Llorens, Andrés Marzal, Moisés Pastor-i-Gadea, Federico Prat, Enrique Vidal, Juan M. Vilar. The EuTrans-I Speech Translation System. Machine Translation, 2000. Vol. 15 pp. 75-103.

The EuTrans project aims at using Example-Based approaches for the automatic development of Machine Translation systems - accepting text and speech input - for limited domain applications. During the first phase of the project, a speech translation system that is based on the use of automatically learnt Subsequential Transducers has been built. This paper contains a detailed and to a long extent self-contained overview of the transducer learning algorithms and system architecture, along with a new approach for using categories representing words or short phrases in both input and output languages. Experimental results using this approach are reported for a task involving the recognition and translation of sentences in the hotel reception communication domain, with a vocabulary of 683 words in Spanish. A translation word error rate of 1.97 % is achieved in real time factor 2.7 in a Personal Computer.