The Translating Telephone has been a major goal of speech translation for many years. Previous approaches have attempted to work from limited-domain, fully-automatic translation towards broad-coverage, fully-automatic translation. We are approaching the problem from a different direction: starting with a broad-coverage but not fully-automatic system, and working towards full automation. We believe that working in this direction will provide us with better feedback, by observing users and collecting language data under realistic conditions, and thus may allow more rapid progress towards the same ultimate goal. Our initial approach relies on the wide-spread availability of Internet connections and web browsers to provide a user interface. We describe our initial work, which is an extension of the Diplomat wearable speech translator.

The Multi-Engine MT (MEMT) architecture combines the outputs of multiple MT engines using a statistical language model of the target language. It has been used successfully in a number of MT research systems, for both text and speech translation. Despite its perceived benefits, there has never been a rigorous, published, double-blind evaluation of the claim that the combined output of a MEMT system is in fact better than that of any one of the component MT engines. We report here the results of such an evaluation. The combined MEMT output is shown to indeed be better overall than the output of the component engines in a Croatian ↔ English MT system. This result is consistent in both translation directions, and between different raters.