Speech to speech machine translation: Biblical chatter from Finnish to English
David A. Ellis, Mathias Creutz, Timo Honkela, Mikko Kurimo · 2008
Speech-to-speech machine translation is in some ways the peak of natural language processing, in that it deals directly with our original, oral mode of communication (as opposed to derived written language). As such, it presents challenges that are not to be taken lightly. Although existing technology covers each of the steps in the process, from speech recognition to synthesis, deriving a model of translation that is effective in the domain of spoken language is an interesting and challenging task. If we could teach our algorithms to learn as children acquire language, the result would be useful both for language technology and cognitive science. We propose several potential approaches, an implementation of a multi-path model that translates recognized morphemes alongside words, and a web-interface to test our speech translation tool as trained for Finnish to English. We also discuss current approaches to machine translation and the problems they face in adapting simultaneously to morphologically rich languages and to the spoken modality. 1