Abstract
Stochastic finite-state transducers constitute a type of word-based models that allow an easy integration with acoustic model for speech translation. The aim of this work is to develop a novel approach to phrase-based statistical finite-state transducers. In this work, we explore the use of linguistically motivated phrases to build phrase-based models. The proposed phrase-based transducer has been tested and compared to a word-based equivalent machine, yielding promising results in the reported preliminary text and speech translation experiments.
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