MiTiN 2013 Keynote in Detroit Michigan

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http://mitin.org/conference/
The Impact of MT on the Translator or MT and the Translator
The session will explore why MT matters and why we can expect it’s use to continue and expand in future even though MT is not suitable for all kinds of translation work. The session will also cover:
· Understanding different kinds of MT
· Examples of where MT is most successful and where not will be given
· What is post-editing, or what are the different variants of post-editing?
· How different is PE from traditional revision?
· How to assess post-editing MT (PEMT) work?
· Critical skills for PE as identified by agencies
· High value roles for translators with MT technology
· Understanding the MT system refinement and improvement process
· PEMT compensation issues
The way forward is (MT + Human) collaboration, not MT alone as the demand for productivity grows.

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MiTiN 2013 Keynote in Detroit Michigan

  1. 1. The Impact of MT on the Translator Kirti Vashee – kirti.vashee@asiaonline.net http://www.twitter.com/kvashee http://kv-emptypages.blogspot.com Copyright © 2009, Asia Online Pte Ltd
  2. 2. Copyright © 2009, Asia Online Pte Ltd
  3. 3. A Content Explosion Across The Globe The Emergence of Social Media and Social Networking as Business Drivers and Influencers New Open Innovation & Collaboration Business Models The Increasing Importance of Technology & Automation A Rising Asian Market Changing Global Enterprise Priorities Copyright © 2009, Asia Online Pte Ltd
  4. 4. More information was created in 2005 than in the previous 40,000 years ! Total Exabytes of Information 40,000 35,000 30,000 25,000 20,000 2009 = 800 Million Petabytes 1 PB = 1,000,000 GB 15,000 10,000 5,000 Copyright © 2009, Asia Online Pte Ltd 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 0 Source: IDC Digital Universe Study, May 2010
  5. 5. As these conversations become increasingly independent of these sites, falling traffic will render them ineffective in their current form. Instead, the online presence of each brand will necessarily expand out into the social space to stay in touch with their audience. Simon Mainwaring Copyright © 2009, Asia Online Pte Ltd
  6. 6. 10X Customer Exceptions 30X X Assisted Support Center Self-Service Web Portal Knowledge Base Development/ Engineering Copyright © 2009, Asia Online Pte Ltd Communities User Initiated Groups Community Conversations Product Management Source: Consortium for Service Innovation
  7. 7. Customer Interactions Corporate Investment and focus Direct Support 1-3% Activity 95% Activity Assisted Support 10,000 @ $250/case Self-Service Support 5-9% Activity 100,000 @ $10/exception Community Support 90-95% of Activity 300,000 @ $1/exception? Indirect Support Copyright © 2009, Asia Online Pte Ltd Source: Consortium for Service Innovation
  8. 8. • Static Reference Material • Long Shelf Life • Just In Case • Mandatory and necessary • Information flow from company to consumer Copyright © 2009, Asia Online Pte Ltd • Real Time Search & Find Mode • Information acquired as needed • Comprehensive & dynamic knowledge base • Continuously Updated • Human Filtered Information • Expert Identification • Trust agent based information gathering • Continuously flowing and changing and often community based
  9. 9.  Global enterprises face a content deluge with dynamic content coming from both internal and external sources  High volumes of content expected to be translated increasingly faster and faster  Customers increasingly in control of marketing and brand messages  A shift from corporate messaging to customer conversations and authentic communications More Content, Faster Turnaround Times, Lower Cost Copyright © 2009, Asia Online Pte Ltd
  10. 10.  What We Translate – More Dynamic Real-Time Content  Why We translate – From Mandatory to Increase and Expand Communication with Customers  How We Translate – More Automation, MT and Open Collaboration Models  Highly Personalized Content to Customers when they need it in a variety of digital forms More Content, Continuous, Faster Turnaround, Cheaper Project Based TEP  Continuous Streams Copyright © 2009, Asia Online Pte Ltd
  11. 11. Example Human Corporate Products User Interface Existing Markets $31.4B New Markets 2,000 Product Brochures 10,000 Software Products 50,000 Manuals / Online Help 200,000 Enterprise Information HR / Training / Reports 500,000 Support / Knowledge Base Copyright © 2009, Asia Online Pte Ltd Corporate Brochures User Documentation Communications Machine Words User Generated Content Email / IM 10,000,000 Call Center / Help Desk 20,000,000+ Blogs / Reviews 50,000,000+
  12. 12. Copyright © 2009, Asia Online Pte Ltd
  13. 13. • Growth in Word Volume for Traditional Localization Projects • Faster Turnaround Time Requirements • Changing Translation Price-Value Expectations • Increasing Acceptance of MT by Enterprise Buyers • New Rapidly Growing Types of Content – – – – Patents & Scientific Content Customer Support & Care Content Customer Conversations User Generated Content Copyright © 2009, Asia Online Pte Ltd
  14. 14. • Traditional Localization Projects – Documentation and Localization • Focused on improving translation productivity • Same quality deliverable but faster and cheaper • New MT Enabled Projects – Patents & Scientific Content • Huge Volume – Hundreds of millions of words – Customer Support & Care Content • Very high value but short-lived • Technical Support & Knowledge base – Customer Conversations • Editing work only, focused on corrections. Copyright © 2009, Asia Online Pte Ltd
  15. 15. Linguistic Translation Quality Target Quality (TEP Level) The effort and linguistic work done to raise RAW MT to target quality levels is PEMT Raw MT Output Quality Common Misperceptions • • • • • The target quality level is always the same as TEP or other HT standards The raw MT output quality is consistent from system to system The corrective effort is always the same from language to language There is little or no “a priori” control on the MT output quality MT error patterns are consistent from segment to segment Copyright © 2009, Asia Online Pte Ltd
  16. 16. Pre-Analysis of Source Material Linguistic Profiling and Identification of Key Patterns Terminology Standards Development Translation Quality Source Cleanup • • • • • Error Pattern Identification Target Quality MT Output Quality Varies Error Pattern Correction Unknown Word Handling Development of Linguistic Rules Expansion of vocabulary Development of TL Style & Expression Data Corrective Feedback Process Development Raw Corrections Amplification MT engines (especially SMT-based ones) get better with feedback MT is not exactly the T of the TEP process MT engines require upfront investments and analysis for best results MT engines differ from language to language (FIGS easier than CJK) MT error patterns can vary from segment to segment Copyright © 2009, Asia Online Pte Ltd
  17. 17. How do you pay post-editors fairly if each engine is different? Tools Needed: • Effective Quality metrics – Automated – Human • Confidence scores – Scores on a 0-100 scale – Can be mapped to fuzzy TM match equivalents • Post Edit Quality Analysis – After editing is complete or even while editing is in progress, effort can be easily measured Copyright © 2009, Asia Online Pte Ltd
  18. 18. MT System Quality Characteristics – Productivity Implications Free Online Engines Can be useful in some languages but often lower productivity than using TM alone and impossible to adapt to specific needs 1,000 to 3,000 Words/ Day per human editor Average segment quality = ~25 to 40% TM Fuzzy Match Human TEP Process Typically produce 2,500 Words / Day per translator Low Quality - Moses Less than 5% of these systems can outperform free online MT and best case productivity may be in the 3,000 Words/Day range Average segment quality = 50% - 60% TM Fuzzy Match Average Expert System These systems can provide 5,000 to 7,000 Words/Day per editor Average segment quality = 60% - 75% TM Fuzzy Match Superior Expert These systems can provide 9,000 to 12,000 Words/Day per editor Average segment quality = 70% - 85% TM Fuzzy Match Exceptional MT Copyright © 2009, Asia Online Pte Ltd These systems can provide 12,000+ Words/Day per editor Average segment quality = 80% - 90% TM Fuzzy Match
  19. 19. Copyright © 2009, Asia Online Pte Ltd
  20. 20. Data Preparation Data Cleaning Translate Training Data Collections Diagnostics and Fine Tuning Quality Assurance Language Pair Foundation Data Customer Translation Data and Linguistic Assets Copyright © 2009, Asia Online Pte Ltd Domain Foundation Data
  21. 21. Your Data Bilingual Translation Memories In domain historical translations in source and target language. Target Language Monolingual Data Monolingual target language text and URLs of in-domain websites. Client 1 2 3 Extra Data (If Available) Bilingual Dictionaries and Glossaries In domain and client specific glossaries and dictionaries. 5 Source Language Non-Translatable Terms Source language terms such as product names and place names that should not be translated. 6 Source Material To Be Translated Source material can be analyzed and processed to further improve quality. Style Guides Rules can be added to match client style guide requirements. Copyright © 2009, Asia Online Pte Ltd Identify Language Pair Identify Top Level Domain Upload Your Data 4 Process Data 7 Train Engine Receive Tuning and Test Set File Select Best 3000 Segments Ready to Translate 8 Asia Online Quality Improvement Plan
  22. 22. LP Source JA-EN なお, 以下の座標系の定義は 以下の通り。 JA-EN JA-EN EN-DE EN-DE EN-DE Human Reference Definitions pertaining to the coordinate systems are given below. せん断試験の管理特性を規定 Are the control characteristics of し判断基準は明確か shearing test defined to specify criteria for judgement clearly? ベントチューブスポット溶接の Is the strength of spot-welds on 強度は確認しているか vent tubes checked? An alternate host can start the Alternative Gastgeber können das meeting and act as the host. Meeting starten und als Gastgeber handeln. You can publish a recorded Sie können eine aufgezeichnete training session that was Schulungssitzung veröffentlichen, created with WebEx Recorder. die mit dem WebEx-Rekorder aufgezeichnet wurde. Once customer approves your Wenn der Kunde Ihre Anforderung request, the customer can select genehmigt, kann er eine an application to share. Applikation zum Teilen auswählen. EN-ES Remove the steel ball from the main oil gallery before cleaning. EN-ES Continuously with the ignition on and the propulsion system active. EN-ES The average response time goal is assigned a specific time goal. Customized Furthermore, the definition of the coordinate systems are as follows. Are the control characteristics of shear test defined to specify criteria for judgement clearly? Is the strength of spot-welds on vent tubes checked? Alternative Gastgeber können das Meeting starten und als Gastgeber handeln. Sie können eine aufgezeichnete schulungssitzung veröffentlichen, die mit dem WebEx-Rekorder erstellt wurde. Wenn der Kunde Ihre Anforderung genehmigt, kann der Kunde eine Applikation zum Teilen auswählen. Retire la bola de acero de la Retire la bola de acero de la canalización de aceite principal canalización de aceite principal antes de limpiar. antes de la limpieza. Continuamente con el encendido Continuamente con el encendido conectado y el sistema de en posición on y el sistema de propulsión activo. propulsión activo. El objetivo del tiempo de respuesta El objetivo del tiempo de medio se asigna a un objetivo de respuesta medio se asigna a un tiempo específico. objetivo de tiempo específico. Foundation Furthermore, the following coordinate system as defined. Shear test criterion for defining characteristics of the clear? It is the intensity of the welding spot vent tubes? Stellvertretendes Gastgeber beginnen können und so zu tun, als die Tagung des Aufnahmelandes. Sie können eine namentliche Fortbildungsveranstaltung veröffentlichen, mit WebEx Fahrtenschreiber. Wenn Verbraucher stimmt ihrem Antrag, der Kunde auswählen können, einen Antrag zu teilen. Eliminar la bola de acero de la limpieza galería antes de petróleo. Continuamente con la ignición en activo y el sistema de propulsión. La meta media del tiempo de respuesta se asigna una meta del momento específico. Customization teaches an engine how to translate using YOUR style and vocabulary Copyright © 2009, Asia Online Pte Ltd
  23. 23. Comparison of Foundation and Custom Engine Output – IT to EN Foundation Engine Output Frame at cherry tree massive (20 millimeter thickness); anticata finishing. Colourless glass, satin, bisellato and decorated. Bodywork in chipboard class E1 (18 millimeter thickness) nobilitato melaminico; finishes cherry tree. Borders on the ABS and edges in such a laminatino; finishes cherry tree. Back pain fibre-( 3 millimeter thick); primer; white. For pivot elements with glass or at the request, MoF (2.5 millimeter thickness) nobilitato melaminico; finishes cherry tree. At the request, flanks on sight in chipboard class E1; veneering with sliced cherry; painting acrylic polyurethane and. Anodized aluminium for sottolavelli and columns refrigerator. Protection from condensation and leakage of water. Release the furniture into the environment. Contact holdings disposing of solid urban waste, in accordance with the municipal regulations waste. For household appliances, consult the SPC with the guarantee. Copyright © 2009, Asia Online Pte Ltd Custom Engine Output Solid cherrywood frame (thickness 20 millimeter); antique finishing. White glass, satin, beveled and decorated. Carcass in Class E1 chipboard (thickness 18 millimeter) melamine-coated panel; cherrywood finishing. Edges in ABS and basic laminate edges; cherrywood finishing. Back Panel of fibre (thickness 3 millimeter); lacquering; white colour. For elements with glass door or upon request, melamine MDF (thickness 2.5 millimeter) coated; cherrywood finishing. Upon request, visible sides in class E1; chipboard veneering with cherrywood sliced veneer; acrylic and Polyurethane painting. Anodised aluminium for under sinks and tall units for built-in fridge. Protection against condensation and water losses. Not dispose of furniture in the environment. Contact the company responsible for disposal of urban solid waste, in compliance with municipal waste management regulations. For household appliances, consult the producer's technical specifications and relevant guarantee.
  24. 24. A method of distilling a polymerizable vinyl compound selected from the group consisting of acrolein, methacrolein, acrylic acid, methacrylec acid, hydroxyethyl acrylate, hydroxyethyl methacrylate, hydroxypropyl acrylate, hydroxypropyl methacrylate, glycidyl acrylate and glycidyl methacrylate, the method comprising distilling the polymerizable vinyl compound in the presence of a polymerization inhibitor using a distillation tower having perforated trays without downcomers and wherein the temperature of the inner wall of the tower is maintained at a temperature sufficient to prevent the condensation of the vapor being distilled, whereby the polymerizable vinyl compound is distilled without the formation of polymer. Actual sample of Japanese to English MT output • • • • Requires a significant terminology database effort Special handling for long sentences Monolingual target language analysis Linguistic parsing Copyright © 2009, Asia Online Pte Ltd
  25. 25. Initial System put into production Changes are collected and added to initial corpus to drive continuous retraining Trained Internal Experts begin initial clean up and correction process All users allowed to suggest changes which goes through vetting process Expert Users also allowed to make changes Post-editing effort and cost can be managed by improving the quality and performance of the MT engine via corrective linguistic feedback Quality Publication Quality Target Post Editing Effort Raw MT Quality 1 Copyright © 2009, Asia Online Pte Ltd 2 3 4 5 6 Engine Learning Iteration
  26. 26. 1 Original Source File Machine Translate Raw Machine Translations Human Post Editing 2 1 2 Post Edited Translations Incremental Quality Improvement Copyright © 2009, Asia Online Pte Ltd Data Analysis and Manufacturing Send Raw MT and Post Edited Translations back to Asia Online Supported File Types
  27. 27. Copyright © 2009, Asia Online Pte Ltd
  28. 28. Translator 1 Translator 2 Translator 3 Translator 4 Words Per Day 0 • • • • Human Only 2,000 MT + Post Editing 4,000 6,000 8,000 10,000 12,000 Productivity improvement results differ by translator. The above data is derived by studying 4 different translators productivity used only human and then with the addition of MT + human post editing by professionals Weaker translators often tend to benefit more from technology Customization is key to minimizing translator frustration Rapid measurement and assessment of quality is key to profitability Copyright © 2009, Asia Online Pte Ltd
  29. 29. MT System Quality Characteristics – Productivity Implications Free Online Engines Can be useful in some languages but often lower productivity than using TM alone and impossible to adapt to specific needs 1,000 to 3,000 Words/ Day per human editor Average segment quality = ~40% TM Fuzzy Match Human TEP Process Typically produce ~2,500 Words / Day per translator Low Quality - Moses Less than 5% of these systems can outperform free online MT and best case productivity may be in the 3,000 Words/Day range Average segment quality = 50% - 60% TM Fuzzy Match Average Expert System These systems can provide 5,000 to 7,000 Words/Day per editor Average segment quality = 60% - 75% TM Fuzzy Match Superior Expert These systems can provide 9,000 to 12,000 Words/Day per editor Average segment quality = 70% - 85% TM Fuzzy Match Exceptional MT Copyright © 2009, Asia Online Pte Ltd These systems can provide 12,000+ Words/Day per editor Average segment quality = 80% - 90% TM Fuzzy Match
  30. 30. Standard TEP Excellent Moses Average Expert Excellent Expert 2,500 3,000 6,000 9,000 Hourly Rate $45 $45 $45 $45 Word Rate 15 cents 12 cents 10 cents 7.5 cents Daily Cost at Hourly Rate $360 $360 $360 $360 Daily Cost at Word Rate $375 $360 $600 $675 $72,000.00 $ 60,000.00 $30,000.00 $20,000.00 $75,000.00 $ 60,000.00 $50,000.00 200.00 166.67 83.33 $37,500.00 55.56 Translated Words / Day 500,000 Word Project Hourly Cost Word Rate Cost Man Days Copyright © 2009, Asia Online Pte Ltd
  31. 31. • The productivity gain or loss can be calculated by counting the average number of words translated per hour. • This productivity information can be used to determine PEMT compensation rate. • Test Example: 4 Hours with 1 Translator (EN > DE) Total Words Words Per Hour Human Translation 1,253 313 MT + Human Post-Editing 4,116 1,029 Difference (+ Gain / - Loss) +2,863 +715 • Productivity Gain: 328% • For a mature custom engine 328% is not uncommon and represents productivity gains similar to using TM fuzzy matches of 75%-80%. • Understand the quality of the MT engine output BEFORE you accept or reject work Copyright © 2009, Asia Online Pte Ltd
  32. 32. Copyright © 2009, Asia Online Pte Ltd
  33. 33. Linguistic Steering Pattern Identification, Corpus Analysis, Linguistic Problem Solver, Quality Assessment, Linguistic Asset Development and Test & Tuning Set Development MT-Savvy Translators & Editors Rapid Error Identification / Correction Manufacture Corrective Data and Drive Early Development of MT Engines Less Skilled Editors with SME and Target Language Skill Can be Monolingual, Students, Housewives Monolingual Data Cleanup N-gram Resolution and Preparation Copyright © 2009, Asia Online Pte Ltd
  34. 34. • Training of post-editors – New Skills – MT Post Editing Is Different to HT Proof Editing • Different error patterns and different ways to resolve issues • Some LSPs are creating e-learning courses for post editors • 3 Kinds of Post Editors – Professional Bilingual MT Post Editors: • Often with domain expertise, these editors have been trained to understand issues with MT and not only correct the error in the sentence, but also create learning material – Early Career Post Editors: • Editing work only, focused on corrections – Monolingual Post Editors • Experts in the domain, but may not be fluently bilingual • With a mature engine, this approach will often deliver the best, most natural sounding results Copyright © 2009, Asia Online Pte Ltd
  35. 35. Machine Translate S Original Source Note: Multiple machine translation candidates can be scored at one time to compare against each other. E.g. Asia Online, Google, Systran C Compare and Score R Human C Translation Reference Candidate 3 Measurement Tools • Human Quality Assessment • Automated Quality Metrics • Sentence Evaluation S – Original Source: • The original sentences that are to be translated. – Human Reference R • The gold standard of what a high quality human translation would look like. – Translation Candidate C • This is the translated output from the machine translation system that you are comparing. Copyright © 2009, Asia Online Pte Ltd
  36. 36. • The test set being measured: Different test sets will give very different scores. Very small test sets can give misleading results. • How many human reference translations were used: If there is more than one human reference translation, the resulting BLEU score will be higher. • The complexity of the language pair: Spanish is a simpler language in terms of grammar and structure than Finnish or Chinese. • The complexity of the domain: A patent has more complex text and structure than a children’s story book. It is not practical to use two different test sets and conclude that one translation engine is better than the other. • The capitalization of the segments being measured: When comparing metrics, the most common form of measurement is Case Insensitive. • The size of the test set: Use 1,000 or more BLIND segments to get good assessments • The measurement software: There are many measurement tools for translation quality. Each may vary slightly with respect to how a score is calculated It is clear from the above list of variations that a BLEU score number by itself has no real meaning. Copyright © 2009, Asia Online Pte Ltd
  37. 37. Evaluation Criteria of MT output Excellent (4) Read the MT output first. Then read the source text (ST). Your understanding is not improved by the reading of the ST because the MT output is satisfactory and would not need to be modified (grammatically correct/proper terminology is used/maybe not stylistically perfect but fulfills the main objective, i.e. transferring accurately all information.) Good (3) Read the MT output first. Then read the source text. Your understanding is not improved by the reading of the ST even though the MT output contains minor grammatical mistakes .You would not need to refer to the ST to correct these mistakes. Medium (2) Read the MT output first. Then read the source text. Your understanding is improved by the reading of the ST, due to significant errors in the MT output . You would have to re-read the ST a few times to correct these errors in the MT output. Poor (1) Read the MT output first. Then read the source text. Your understanding only derives from the reading of the ST, as you could not understand the MT output. It contained serious errors. You could only produce a translation by dismissing most of the MT output and/or re-translating from scratch. Copyright © 2009, Asia Online Pte Ltd
  38. 38. Human evaluators can develop custom error taxonomy to help identify key error pattern problems . Copyright © 2009, Asia Online Pte Ltd
  39. 39.  Corpus Analysis & Preparation  Pattern Identification  Linguistic Structural Analysis  Linguistic Problem Solving  Linguistic Production Process Management  Translation & MT Engine Quality Assessment  Rapid Quality Assessment  Effective Use and Development of Automated Measurements  Steering Guidance to MT Developers  Rapid Error Detection & Correction  Open minded translators  Better translator workbenches and tools  Skilled monolinguals with subject matter expertise (SME)  Community Management  Recruiting  Quality Management Copyright © 2009, Asia Online Pte Ltd
  40. 40. Just a short walk from Times Square The following n-grams, or word strings, can be generated from this sentence. 1 Gram Just a short walk from times square 2 Grams just a a short short walk walk from from times times square 3 Grams just a short a short walk short walk from walk from times from times square 4 Grams just a short walk a short walk from short walk from times walk from times square Identify high frequency phrases (n-grams) to translate Copyright © 2009, Asia Online Pte Ltd 5 Grams just a short walk from a short walk from times short walk from times square
  41. 41. Before Machine Translation Source text is processed and modified. Pre-Translation Corrections (PTC) - A list of terms that adjust the source text fixing common issues and making it more suitable for translation. Non-Translatable Terms (NTT) - A list of monolingual terms that are used to ensure key terms are not translated. Runtime Glossary (GLO) - A list of bilingual terms that are used to ensure terminology is translated a specific way. After Machine Translation Target text is processed and modified. Post Translation Adjustment (PTA) - A list of terms in the target language that modify the translated output. This is very useful for normalization of target terms. Each of the above runtime customizations can be applied in 2 forms: Default: Applied to all jobs. Job Specific: A different set of customizations can be applied for different clients. Copyright © 2009, Asia Online Pte Ltd
  42. 42. Original Source Corrected Source PrecisionTMWorkstations Precision™ Workstations ChinaSingaporeSydney China, Singapore, Sydney Hyper-VTM Hyper-V™ 6TBExternal 6TB External w/ with TO Q1 TO QUESTION 1 — <wall/>:<wall/> (d)'|"(?=[ ](HD|disp|SAS|SATA)) ${1}-inch • Support for case sensitive and case insensitive matches • Support for regular expressions Copyright © 2009, Asia Online Pte Ltd
  43. 43. Term New York Times PCs Limited Asia Online Pte Ltd Fortune 500 John Jacob Microsoft Office Cisco Local Director Man Yee Wai Copyright © 2009, Asia Online Pte Ltd
  44. 44. Original Source Specified Translation Portugal-Portuguese Portugais (Portugal) Independent Software Vendor (ISV) éditeurs de logiciels indépendants (ISV) South Holland Province La Province Hollande-Méridionale Proof of Concept (POC) engagement mission de validation technique HBA adaptateur de bus hôte Fine print Clauses complémentaires Standup HBA adapter pour adaptateur de bus hôte HBA standup adapter pour adaptateur de bus hôte Copyright © 2009, Asia Online Pte Ltd
  45. 45. Original Target Adjusted Target double port 2 port double-port 2 port deux port 2 port deux-port 2 port I5 i5 e/s E/S cloud computing Cloud Computing ompm OMPM Copyright © 2009, Asia Online Pte Ltd
  46. 46. Content Type Target Quality Process Volumes Legal, Marketing, Mandatory High Human Translation, TEP Low Reference, KB Moderate Custom MT + Professional PostEditing High User Generated Content Moderate to Low Custom MT + Community PostEditing Very High Random Corporate Content Low - Gisting Custom Corporate MT High Random Web Content Low - Gisting Free MT 150 Billion Words in Google Translate in 2010 Match the production process to the value, volume and quality configuration of the content Copyright © 2009, Asia Online Pte Ltd
  47. 47. Internal Corporate Content • Product Training Materials • Manuals & Documentation • Design & Research • Sales & Marketing • Emails & Website External Partner & Customer Content • Training Materials • Customer Feedback • Customer Care & Support • Customer Blogs & Forums • Social Network Content Prioritize for Translation Process Develop Linguistic Profiles of Key Content Build and Leverage Linguistic Assets for Translation Production Lines Different Target Quality: TEP, MT+ Post Editing, Custom MT, Raw Corporate Baseline MT Customize MT Engine Communicate Simplify & Clean Translate & Refine MT Engine Listen & Learn Distribute & Share Copyright © 2009, Asia Online Pte Ltd Analyze Source Post-Edit and Correct
  48. 48. Copyright © 2009, Asia Online Pte Ltd
  49. 49. • What content has the greatest value for our target audience? • How do we get it translated quickly, at the highest quality possible at the lowest cost possible? • How do we build infrastructure that enables emerging new content to be quickly translated as needed? • From localization projects to flowing streams of high value customer related content Copyright © 2009, Asia Online Pte Ltd
  50. 50. Any Agency not using MT competently in 5 years time will be marginalized or be a niche player. In 5 years time, leading Agencies will be translating more content in 1 year than in the previous 5 years combined. There will be more demand for translators than ever before, but roles will evolve and change. Copyright © 2009, Asia Online Pte Ltd
  51. 51. www.kv-emptypages.blogspot.com Thank You Kirti Vashee – kirti.vashee@asiaonline.net Follow Me on Twitter: @kvashee Join the Automated Language Translation Group in LinkedIn Copyright © 2009, Asia Online Pte Ltd

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