Towards speech translation of non written languages

A large amount of languages in the world do not have an acknowledged written form. However, for a task like speech to speech translation, the written form of a language may be considered as secondary and it might be possible, under certain conditions, to bypass it. This paper is our first attempt to show that such an approach is possible. We propose a phone-based speech translation approach where translation models are learned on a parallel corpus made of foreign phone sequences and their corresponding English translation. Our experiments show that using our so-called phone-based approach leads almost to the same performance as the baseline approach, while being theoretically applicable to any non written language.