This work implements a novel formulation for phrase-based translation models making use of morpheme-based translation units under a stochastic finite-state framework. This approach has an additional interest for speech translation tasks since it leads to the integration of the acoustic and translation models.
As a further contribution, this is the first paper addressing a Basque-to-Spanish speech translation task. For this purpose a morpheme based finite-state recognition system is combined with a finite-state transducer that translates phrases of morphemes in the source language into usual sequences of words in the target language.
The proposed models were assessed under a limiteddomain application task. Good performances were obtained for the proposed phrase-based finite-state translation model using morphemes as translation units, and also notable improvements are obtained in decoding time.
Index Terms: Speech Translation, Stochastic Finite- State Transducers, Morphology