The picture seems less sparkling when we look at speech translation. Even in a simple approach, in which first-best recognition result is fed into a text translation system the improvements in speech recognition and in machine translation will result in improved speech translation. There has been quite some work on tighter coupling between the two components, like lattice translation, using ASR features in MT and optimizing the end-to-end performance, it still seems to be once-in-a-while improvements which result from this work. Additional topics relating to speech translation are disfluency removal, segmentation and automatic punctuation.

The panel discussion will take a critical look at recent work in speech translation:

• what has been done?
• what improvements have been reported?
• how solid are these improvements?
• Are there any important aspects of speech translation which have been completely overlooked or are deemed to be important but beyond the reach of our current technologies?
• Are there additional requirements when speech translation is not an end but the output fed into other systems, like question answering systems?
• How close are we to useful applications of speech translation technology?