Thinking Strategically
About Content
Destined for Machine
Translation
Val Swisher
Founder & CEO
@contentrulesinc

© 2013. ...
Who Am I?

 Founder and CEO of Content Rules
 25+ years in content arena
 Specialty areas:
 Global content strategy
 ...
What is Content Rules?
 Professional services firm specializing in:
• Content strategy / Global content strategy
• Conten...
Global Readiness
 Ensure content is translatable




Readability
Grammar and style
Reuse

 Evaluate and improve conte...
© 2013. Content Rules, Inc. All rights reserved.
Today’s Presentation







Importance of content
Historic background
Types of machine translation
Content quality a...
Content Is Important

87% of respondents to a recent CMO Council survey said that content had
a moderate to major impact o...
Content Is A Strategic Asset

© 2013.

Content Rules, Inc.
All rights reserved.
What Does It Mean to be Strategic?
stra·te·gic
[struh-tee-jik]
adjective
1. pertaining to, characterized by, or of the
nat...
Content Creation In the Past

 Content wasn't so easy to create and distribute
 Created by trained professionals
 Only ...
Content Creation Today

 Everyone creates content

 Very easy to distribute
 Now, we have loads and loads of content
• ...
Translation In The Past

 Content wasn't so easy to translate.

 Trained professionals
 Only they understood multiple
l...
Translation Today
 It is easy and free to translate content
 We have loads and loads of translated content
•

Some of it...
More Machine Translation All The Time
 Machine Translation (MT) is becoming more relied upon as a way to
get cost-effecti...
Source Content And Machine Translation

 Types of MT engines and the effect of source content
on them
 What are Bleu sco...
MT Engine Types

There are three types of MT Engines:
1. Rule-based
2. Statistical
3. Hybrid

© 2013.

Content Rules, Inc....
Rule-Based MT (RBMT)






Uses linguistic rules
Extensive use of bilingual dictionaries
Transfers structure of sourc...
Statistical MT (SMT)







Based on analysis of content
Engine trained over time
More content = better results
Need...
Hybrid






Combines rule-base and statistical
Provides predictability and consistency of RBMT
Provides fluency and f...
Training The SMT Beast

 Training SMT software extremely important
 Poor quality source = Poor quality translations
 So...
The Effect Of Poor Content On SMT And
Hybrid MT

 Poor or unpredictable translations
 Increased time to retrain the syst...
Evaluating MT Precision - Bleu Scores

 Introduced in 2002 by the IBM Watson Research Center
 Automatic evaluation metri...
Bleu Scores – Helpful Or Hype?
According to Callison-Burch, Osborne, and Koehn of the School on
Informatics, University of...
That’s Okay. We Can Post Edit.

Original
Source
Content
Post-Edited
Translations

© 2013.

Content Rules, Inc.
All rights ...
Why Not Pre-Edit Instead?






Fewer issues = less post editing
Save time
Save money
Improve quality

© 2013.

Conten...
Create Global-Ready Content







Reduce word count
Standardize terminology
Enforce correct grammar
Eliminate jargon...
Results of Pre-Editing







Save money
Improve quality
Faster time to market
Fewer in-country iterations
Better tra...
Summary







Content is a strategic asset
Machine translation is becoming more popular
Poor quality content incorre...
Val Swisher
vals@contentrules.com
@contentrulesinc
© 2013.

Content Rules, Inc.
All rights reserved.
Val Swisher
CEO & Founder
vals@contentrules.com
@contentrulesinc
© 2013.

Content Rules, Inc.
All rights reserved.
Reduce word count

 We recommend 24 words, max, for machine translation.
 It is impossible for people to understand long...
Let's say we have 100,000 words of source content.
We are going to translate the content into 14 languages.
We will end up...
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Thinking Strategically About Content Destined for Machine Translation

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It's a fact. More and more organizations are exploring the benefits of machine translation. Some people believe automated translation will be ubiquitous; part of every system we use to interact with content — tablets, smart phones, mobile devices, computer kiosks, bank machines, consumer electronics, appliances, automobiles, trains, buses and planes. But, is our content ready for machines to process? Can automated translation systems produce the quality we desire? And, if so, what do we need to do to prepare it? Attend this session to learn how thinking strategically about your content can help you make smart decisions up front that will provide big benefits downstream. Learn how creating structured, semantically-rich content today can help you feed automated translation systems tomorrow.

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  • According to the CMO Council and Netline in their June 2013 survey, “Understanding How BtoB Buyers Source, Value, and Share Content Online,” 87% of respondents stated that content had a moderate to major impact on their buying decisions.For far too long, content has been treated as something that simply describes, positions, or touts a product. Technical content, in particular, has long been an after thought, something not deemed important. If we don't treat content as a strategic asset, it is just garbage. And if we put garbage into machine translation, it is just exponentiated garbage.
  • One poorly written source document = many poorly translated resulting documentsPoor source content = more post editing Problems exponentiate based on number of language pairs
  • Thinking Strategically About Content Destined for Machine Translation

    1. 1. Thinking Strategically About Content Destined for Machine Translation Val Swisher Founder & CEO @contentrulesinc © 2013. Content Rules, Inc. All rights reserved.
    2. 2. Who Am I?  Founder and CEO of Content Rules  25+ years in content arena  Specialty areas:  Global content strategy  Terminology management  Content quality  Single-sourcing / XML / DITA  Finishing third book, “Global Content Strategy,” due out in 2014 © 2013. Content Rules, Inc. All rights reserved.
    3. 3. What is Content Rules?  Professional services firm specializing in: • Content strategy / Global content strategy • Content creation • Content quality / Global readiness     Based in Silicon Valley Founded in 1994 Acrolinx Authorized Services Provider Authorized provider of The Rockley Strategic Method™ © 2013. Content Rules, Inc. All rights reserved.
    4. 4. Global Readiness  Ensure content is translatable    Readability Grammar and style Reuse  Evaluate and improve content quality using state-of-the-art tools     Reports Metrics Recommendations Fixes  Save money on translation © 2013. Content Rules, Inc. All rights reserved.
    5. 5. © 2013. Content Rules, Inc. All rights reserved.
    6. 6. Today’s Presentation       Importance of content Historic background Types of machine translation Content quality affects machine translation results Bleu scores Pre-editing instead of post-editing © 2013. Content Rules, Inc. All rights reserved.
    7. 7. Content Is Important 87% of respondents to a recent CMO Council survey said that content had a moderate to major impact on their buying decisions © 2013. Content Rules, Inc. All rights reserved.
    8. 8. Content Is A Strategic Asset © 2013. Content Rules, Inc. All rights reserved.
    9. 9. What Does It Mean to be Strategic? stra·te·gic [struh-tee-jik] adjective 1. pertaining to, characterized by, or of the nature of strategy: strategic movements. 2. important in or essential to strategy. 3. forming an integral part of a stratagem: a strategic move in a game of chess. © 2013. Content Rules, Inc. All rights reserved.
    10. 10. Content Creation In the Past  Content wasn't so easy to create and distribute  Created by trained professionals  Only they had access to the content © 2013. Content Rules, Inc. All rights reserved.
    11. 11. Content Creation Today  Everyone creates content  Very easy to distribute  Now, we have loads and loads of content • Some of it good • Some of it mediocre • Some of it downright awful © 2013. Content Rules, Inc. All rights reserved.
    12. 12. Translation In The Past  Content wasn't so easy to translate.  Trained professionals  Only they understood multiple languages well enough to translate content © 2013. Content Rules, Inc. All rights reserved.
    13. 13. Translation Today  It is easy and free to translate content  We have loads and loads of translated content • Some of it good • Some of it mediocre • Some of it downright awful © 2013. Content Rules, Inc. All rights reserved.
    14. 14. More Machine Translation All The Time  Machine Translation (MT) is becoming more relied upon as a way to get cost-effective, fast translations  %18.05 year-over-year growth of MT expected over next 3 years*  Must pay a more attention to the source content that goes into it  A machine cannot figure what we meant to say based on what we actually wrote  Garbage In – Garbage Out *http://www.researchandmarkets.com/research/2gpj3p/global_machine © 2013. Content Rules, Inc. All rights reserved.
    15. 15. Source Content And Machine Translation  Types of MT engines and the effect of source content on them  What are Bleu scores  How quality of content affects MT output © 2013. Content Rules, Inc. All rights reserved.
    16. 16. MT Engine Types There are three types of MT Engines: 1. Rule-based 2. Statistical 3. Hybrid © 2013. Content Rules, Inc. All rights reserved.
    17. 17. Rule-Based MT (RBMT)      Uses linguistic rules Extensive use of bilingual dictionaries Transfers structure of source language into target language Results are literal translations based on rules Does not handle ambiguity well (word or phrase having more than one meaning) © 2013. Content Rules, Inc. All rights reserved.
    18. 18. Statistical MT (SMT)       Based on analysis of content Engine trained over time More content = better results Need at least 2,000,000 million words per domain Better quality content = better results Results are more natural translations, based on previous source | destination pairs  Google Translate © 2013. Content Rules, Inc. All rights reserved.
    19. 19. Hybrid     Combines rule-base and statistical Provides predictability and consistency of RBMT Provides fluency and flexibility of SMT Reduces the amount of data needed to train the engine © 2013. Content Rules, Inc. All rights reserved.
    20. 20. Training The SMT Beast  Training SMT software extremely important  Poor quality source = Poor quality translations  Some companies have such poorly trained MT engines that fixing the content first is actually not an option  The engine has been trained to translate poor quality source © 2013. Content Rules, Inc. All rights reserved.
    21. 21. The Effect Of Poor Content On SMT And Hybrid MT  Poor or unpredictable translations  Increased time to retrain the system with correct information  Increased post-editing, per language  Wasted money © 2013. Content Rules, Inc. All rights reserved.
    22. 22. Evaluating MT Precision - Bleu Scores  Introduced in 2002 by the IBM Watson Research Center  Automatic evaluation metric used to compare MT output with reference human translation “The closer a machine translation is to a professional human translation, the better it is.” *  Metric widely used throughout the industry *http://acl.ldc.upenn.edu/P/P02/P02-1040.pdf © 2013. Content Rules, Inc. All rights reserved.
    23. 23. Bleu Scores – Helpful Or Hype? According to Callison-Burch, Osborne, and Koehn of the School on Informatics, University of Edinburgh, Bleu scores have many issues*:  Synonyms and paraphrases difficult to score  All words are weighted equally  Difficult to calculate *http://homepages.inf.ed.ac.uk/pkoehn/publications/bleu2006.pdf © 2013. Content Rules, Inc. All rights reserved.
    24. 24. That’s Okay. We Can Post Edit. Original Source Content Post-Edited Translations © 2013. Content Rules, Inc. All rights reserved.
    25. 25. Why Not Pre-Edit Instead?     Fewer issues = less post editing Save time Save money Improve quality © 2013. Content Rules, Inc. All rights reserved.
    26. 26. Create Global-Ready Content      Reduce word count Standardize terminology Enforce correct grammar Eliminate jargon and colloquialisms Increase reuse © 2013. Content Rules, Inc. All rights reserved.
    27. 27. Results of Pre-Editing      Save money Improve quality Faster time to market Fewer in-country iterations Better translation consistency © 2013. Content Rules, Inc. All rights reserved.
    28. 28. Summary      Content is a strategic asset Machine translation is becoming more popular Poor quality content incorrectly trains MT engines Poor quality content results in increased post-editing Pre-editing saves money and time, and improves translation quality © 2013. Content Rules, Inc. All rights reserved.
    29. 29. Val Swisher vals@contentrules.com @contentrulesinc © 2013. Content Rules, Inc. All rights reserved.
    30. 30. Val Swisher CEO & Founder vals@contentrules.com @contentrulesinc
    31. 31. © 2013. Content Rules, Inc. All rights reserved.
    32. 32. Reduce word count  We recommend 24 words, max, for machine translation.  It is impossible for people to understand long sentences. Imagine software having to parse through all of those commas (half of which are probably missing or misplaced). © 2013. Content Rules, Inc. All rights reserved.
    33. 33. Let's say we have 100,000 words of source content. We are going to translate the content into 14 languages. We will end up with 1.4 million words of content. Let's say the 100,000 words contain all types of errors. We will have to post-edit and fix 1.4 million words on the other side. Let's say we have to pay someone <<<$ .xx>>> per word to post-edit the content. That's <<<$.xx>>> * 1,400,000 words. If we paid <<<$ .07>>> per word to predit the content, we would have spent $7,000 for preparation. © 2013. Content Rules, Inc. All rights reserved.
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