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IWSLT 2007 - Panel

Explore the evolving landscape of Machine Translation in the next 5-10 years, from reliable translations to improved MT applications. Discover neglected research areas, emerging possibilities, and the need for collaboration. Uncover worries and changes in MT systems and research paradigms. Join the conversation on pushing the boundaries of MT technology.

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IWSLT 2007 - Panel

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  1. IWSLT 2007 -Panel 16 Oct 2007

  2. What are the new applications of Machine Translation in 5-10 years? • What is currently not doable, but on the horizon? • What applications will improved MT performance make possible? • What research has to be carried out to get there? • What lines of research are currently neglected but are essential? • Who will make these new applications a reality (academia / commercial)? • Do we have to change the way we do research (e.g. are systems becoming to big for individual researchers or small teams)?

  3. What is currently not doable, but on the horizon? • Reliable translations • We see many good translation, but also many bad ones • Human translators are more consistent • Translation in everyday application • Tourism (very close) • Webchat (moving target)

  4. What applications will improved MT performance make possible? • All those applications we dream of • Ordering vegetarian food in a local Japanese restaurant(well, there may be no vegetarian food;-) • Reading and understanding that sign at the shop in Thailand • Communicating with the doctor in England about some health problems my little son has (9 years of school English didn’t prepare me all that well for this kind of situation!) • All those applications others dream of • Simultaneous translations in the European parliament • Translating news, conversations, blogs, emails, etc for intelligence • Communicating with the local people in a disaster area, or even with the immigrant family in desperate need of help

  5. Are we doing the right thing? • What research has to be carried out to get there? • What lines of research are currently neglected but are essential? • That’s a strange thought: • We neglecting something, which might be essential? • No way!!!

  6. Continued progress What DARPA wants Bleu Tougher Task ahead of us

  7. Who will make these new applications a reality (academia / commercial)? • Applications, not just demos – that’s need to be done by companies • Academia needs to push the field • New ideas, which are shared (in meetings like this one) • Comparison between techniques (in open evaluations)

  8. Do we have to change the way we do research? (Are systems becoming to big for individual researchers or small teams) • Our research is just fine • Progress over the last 10 years was good • Comparative evaluations and dedicated workshops (IWSLT, SMT-Workshop, NIST evaluation) are pushing the field • But we need predictable funding • 3++ years per project • Not DARPA style: terminate project in the middle of the funding period • Yes, some systems become too large for small teams

  9. Some Changes • Large system need a lot of engineering • Parallel computing • Tools for processing data • Incremental training • Covering many more languages • Esp. minority languages • Data collection: bring the (potential) user into the pipline • Looking into usability (rather then Bleu Deltas) • Are translation systems trained on small corpora useful at all?

  10. Some Worries • Surprising results • Increasing training corpus by <2% gives 6-8 Bleu points improvement • Merging sentences into one line gives up to 2 Bleu points • Randomness • What works for one language doesn’t work for another • What worked last year does not help anymore this year • Tuning on different dev sets can give very different performance • Large impact of heuristics • Viterbi alignment combination • “Manual” restrictions needed • Lattice pruning, smaller beam, less reordering gives better results

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