Sustained healthy rates of economic growth in many parts of Asia are helping to swell the middle classes in the region. We can expect to see rising levels of demand for translation into and across the region’s languages for sometime to come.
It’s unlikely that we humans alone will have the capacity to satisfy such demand. Machine translation, with all its adequacies, will undoubtedly play a pivotal role in aiding communication and fueling cross border trade.
We have published articles, videos and reports covering self-service MT implementation for some time. In our reports, we have covered manager’s decision making process, technical implementation, data selection and cleaning, quality evaluation, as well as the outcomes of research into usage and requirements.
Videos provide valuable information on lessons learnt and best practices among early adopters.
Now that collaboration and sharing are firmly on the translation industry agenda, it is imperative that the community develops user-friendly solutions to implement or work around the many technical standards that enable – yet also put the brakes on - efficiency and savings.
The most significant academic event in computational linguistics, the Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, took place in June 2011. The breakthroughs presented in this highly competitive conference often define the future of computational linguistics for years to come.
Last year, we interviewed Laurie Gerber for the article "What machines can’t translate…yet?" where she explained the current limitations of MT technology. Here I focus on two research papers from the ACL event, which stood out in this context. These try to tackle the challenges that arise when translating morphologically rich languages or language combinations where there is a great deal of word reordering needed during translation. I also review a third paper investigating a new avenue for automatically measuring MT quality. This is one of the most promising new approaches in this research area for sometime. If you are interested in understanding the basics of MT quality evaluation, you may find it useful to read the article by Alon Lavie on the “Essentials of machine translation evaluation” first.
How to translate‘cloud computing’, ‘cell phone’or ‘crowdsourcing’ in your language?
Many translators will use Google, Linguee, TAUS Search or a similar search tool and these will sieve through the data to find the answers. There’s knowledge in the data,and we have oceans of it.
At TAUS we're forward-thinking. Which means we try to know our history. So explore with us the story of translation automation in the digital age. See timeline
Researchers debate on future translation technologies
Researchers focus on a myriad of nuances in search of improvements. Major research groups and leading global researchers help to ground us in reality and help shed light on what we can expect in the near future.
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