As contents published on the Internet are becoming more and more dominated by videos, requirements on the language translation have also changed. Specifically, video publishers and distributors have a significant interest in balancing both the translation time and the accuracy. To this end, Pactera has invested in solutions, which leverage machine translation to reduce the overall translation time, and recruit human translators to improve the accuracy in a Wikipedia-like fashion. At Pactera, we aim to help video contents to reach billions of people that were not possible before.

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Balancing Translation Time and Accuracy
for Video Content
Xiao Yuan (Pactera Technology Limited)

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 A daily average of 2
hours on watching
online video per user
 YouTube has more
than 1 billion videos
with machine-
translated captions
Can Machine Translation Solve All Problems?
 Minimize the cost and
the time in fixing
machine translation
errors
Industry Trend Challenges

3. An Example of “Bad” Machine Translation (1)
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4. An Example of “Bad” Machine Translation (2)
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5. How To Choose The Right Translation?
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Pactera
translators
Crowdsourced
feedback
Machine
translation
Pactera judging
system
• Based on our PactWork
crowdsourcing platform
• Text analysis

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7. What We Have Achieved So Far
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Technology
Integration
6000+
Hours of Videos
200+
Languages
20000+ language
Specialists

8. Conclusion
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We estimate to help customers save more than 50% of
costs in translation
While machine translation can quickly translate a large
amount of online video content, it is still not perfect
Pactera provides crowdsourcing platform to improve the
machine translation accuracy from 60% to > 90%
Quality
Cost
Accuracy

9. Xiao Yuan
Localization Director China Division
xiao.yuan@pactera.com
WeChat ID: 18910015818