ELSE IF 2019: Language Technology Market: State-of-the-Art, Trends and Value Propositions
- 1. CROSSLANG COMPANY PROFILE • Independent consultants and systems integrators • Dedicated to Translation Automation Technology • Founded in 2002 • Based in Gentbrugge, Belgium Consultancy Solutions Language audits Translation Management Systems Pilots and Proof of Concepts Terminology Management Programme Management Machine Translation
- 2. LANGUAGE TECHNOLOGY MARKET: STATE-OF-THE-ART, TRENDS AND VALUE PROPOSITION SMART 2016/0103
- 3. CONTEXT AND OBJECTIVES • SMART 2016/0103 is a service contract supporting the EC in implementation of Automated Translation building block • Overall objective: § Contribute to the development of CEF Automated Translation as “multilingualism enabler” (beyond simple translation) for: o CEF DSIs & Online services linked to CEF DSIs o Other relevant public online services
- 4. SMART 2016/0103 Lot 1 (2018) Study on service portfolio development and business case for CEF Automated Translation (“Market Study”) Lot 2 (2018-2020) Implementation of the ‘service desk’ part of the CEF Automated Translation platform and a program support action (“Service Desk”)
- 5. T1 Analysis of the LT market at EU T2 Competitiveness analysis in at least three areas of LT T3 Analysis of LT services used by public administrations in the EU T4 Identification of the value proposition of CEF eTranslation FACTS & FIGURES OPINION OF THE CONSORTIUM
- 6. TASK 1. SUPPLY SIDE ANALYSIS • Objectives § Sizing the market and identifying the main trends § Estimating the number of LT related companies, including market shares and revenues § Identifying existing offering of LT tools/services • Approach § Desk research and IDC’s Software Tracker § Through online questionnaires & telephone interviews
- 7. TASK 1. SUPPLY SIDE ANALYSIS Updated list of LT vendors per country and per type of technology • Translation Technology: MT, TM, TMS • Speech Technology: ASR, Synthesis • Search Technology: Multi-lingual & Semantic search • Natural Language Understanding: Chatbots, Anonymization, Virtual assistants • Analytics: Text analytics, Keyword extraction, Sentiment analysis
- 8. LANGUAGE TECHNOLOGY FORECAST 2018-2020 In EUR million 2018 2019 2020 Germany 197 217 240 United Kingdom 189 209 232 France 88 96 105 Netherlands 55 60 66 Rest of EU 28 249 277 305 778 859 948
- 9. LT VENDORS / EMPLOYEE NUMBERS
- 10. LT VENDORS / TURNOVER In EUR million
- 11. LT VENDORS / PROFITABILITY
- 12. LT VENDORS / REVENUE GROWTH 2019 - 2020
- 13. MOST CITED EMERGING TECHNOLOGIES • Chatbots • Machine Translation • Automatic Summarization • Natural Language Processing • Automatic Speech Recognition
- 16. GOOGLE I/O 2018
- 19. TASK 2. COMPETITIVENESS ANALYSIS Objectives • Conduct a competitiveness analysis • Identify possible shortcomings and opportunities for the European LT market Approach • An analysis of 7 dimensions of the LT market within each of the three domains (score card) • SWOT analysis from European perspective
- 20. Research Innovation Investments Market DominanceIndustry Infrastructure Data Europe North America Asia MACHINE TRANSLATION
- 21. Research Innovation Investments Market DominanceIndustry Infrastructure Data Europe North America Asia SPEECH TECHNOLOGY
- 22. Research Innovation Investments Market DomianceIndustry Infrastructure Data SEARCH TECHNOLOGY Europe North America Asia
- 23. • Research is based on : § Research centres § Research Publications (Scopus database – industry & academia) § Organisational infrastructure (eg. Associations, networks, infrastructures) RESEARCH
- 24. RESEARCH IN MT § Research Centres in Europe : 54 (vs. 23 in US and 14 in Asia) § Publications in Europe : 1752 (vs. 975 in US and 1932 in Asia) § Organisational Infrastructure : EAMT/ELRC/LT Innovate/TAUS/META-NET/CLARIN/ ELEXIS/DARIAH/Toolkits (Moses, Nematus, Open NMT, Marian) Per Country: Per institute/university: Spain 293 DCU 162 Germany 266 Politecnica de Valencia 65 UK 266 Edinburgh 58 Per Author: Per private organization: Way A. 75 DFKI 54 Casacuberta F. 45 FBK 54 Specia L. 44
- 25. • Innovation is based on : § Market of origin of most popular tools o Eg. CAT tools (Across, Déjà Vu, Matecat, memoQ, Memsource, ..) § Implementation of latest techniques o Eg Adoption of NMT : European companies were quick to follow Google and Facebook § Emergence of start-ups o https://angel.co INNOVATION
- 26. Regional distribution of translation technology start-up companies
- 30. • Investments are measured through: § M&A activity § Venture Capital / Financing of companies INVESTMENTS
- 31. • “The European HLT industry is mainly made up by innovative smaller companies (..). Although most of them have been established in the market for several years, the fragmentation of the LT market in Europe (..) hamper their growth. The transformation into global players (..) requires financing in all stages of business life cycle, not only in research activities.” (European Parliament, 2017, p. 104) INVESTMENTS
- 35. • ‘Market Dominance is measured by strength of a brand, product, service or firm’ • Comparing total web traffic of largest providers of LT services MARKET DOMINANCE
- 41. • Market capitalization / Market revenues • Number and size of LT companies “Like Google, Microsoft, Baidu, and Yandex, these Internet giants do not primarily make money from the MT technology itself but their investments and offerings have of course a disruptive and innovative effect on the MT market.” (TAUS, 2017, p. 27) INDUSTRY
- 43. • Availability of technical infrastructure • Access to infrastructure INFRASTRUCTURE
- 46. • Availability of open data § EU institutions, European Open Data Portal § Large national corpora (Bulgaria, Croatia, Slovenia, ..) § Corpora developed by European universities (Opus corpora, ..) § ELRC • Legal regulation of data usage § GDPR regulation is more restrictive • Access to proprietary data resources § Global dominance allows big tech to harvest unmatched amounts of data DATA
- 48. TASK 2. COMPETITIVENESS ANALYSIS Europe North America Asia Machine Translation 14 19 9 Speech Technology 13 20 9 Search Technology 13 19 10 TOTAL 40 58 28
- 49. TASK 3. DEMAND SIDE ANALYSIS WITHIN PUBLIC SECTOR • Objectives § Analysis of LT-based Services and Solutions CURRENTLY in use in Public Administration in the EU § Identification of needs and future requirements • Approach § Identify all different domains of public sector § Obtain results through online questionnaire
- 50. TASK 3. DEMAND SIDE ANALYSIS WITHIN PUBLIC SECTOR Results based on 80 respondents • Low current demand for LT solutions • Translation Technology is most frequently used technology… • .. followed by OCR, Speech and Search • Major vendors cited are US based (exception: CAT tools) • Low collaboration with academia • Optimistic views on new technologies to be incorporated from 2020 and beyond
- 51. TASK 4. IDENTIFICATION OF THE VALUE PROPOSITION • Objectives § Identify value proposition of CEF eTranslation § Assess potential avenues (development, sustainability, …) • Approach § Business model canvas § Input from Tasks 1, 2 and 3 § Input from focused meetings with DSIs
- 52. TASK 4. IDENTIFICATION OF THE VALUE PROPOSITION Today’s situation • Services offered : § Provide an (asynchronous) MT service: secure & integrated/stand-alone § Provide a customer Service Desk § Provide a language resource repository (ELRC-SHARE) § Focus on DSIs and Public Administrations – help them make their service/ content multilingual • Key partners: DGT, DIGIT • Fixed cost structure • No revenue streams
- 53. TASK 4. IDENTIFICATION OF THE VALUE PROPOSITION Potential avenues • Extend current business model Ø Scale up service / Offer real-time translations Ø Customize MT with special attention to under-resourced languages Ø Offer LT services : NER/Anonymization, Quality Estimation, .. • Focus on Governance Ø Provide data for training models : Euramis !! Ø Extra promotion through CEF Telecom calls Ø Provide MT models / LT models (API access)
- 54. CONCLUSIONS & RECOMMENDATIONS • Market is disrupted by dominant global players • MT market evolved in non-core environment Ø Google, Baidu, Yandex : MT to sell adds Ø eBay, Amazon, Alibaba : MT to drive e-commerce Ø SDL : MT to drive localization business • Significant areas of market deficiency Ø Quality gap for smaller and complex languages Ø Domain and application specific MT Ø Security and privacy concerns
- 55. CONCLUSIONS & RECOMMENDATIONS • Europe is strong in research & innovation, but not successful to scale innovations and capture the market • Europe needs European alternatives to fill the gaps/deficiencies and to avoid reliance from market monopolies • Multilingual DSM should be developed on own infrastructure • Public procurement can be the major driver for European LT industry to avoid dependence on existing monopolies
- 56. CONCLUSIONS & RECOMMENDATIONS • Review of IPR regulation of data (fair use of copyrighted data) • Initiatives needed to avoid brain drain • Closer collaboration between Industry - EC
- 63. THANK YOU!