ICT Media

Language Translation Software: Market Shares, Strategies, and Forecasts, Worldwide, 2013 to 2019

  • WIN178738
  • 437 Pages
  • May 2014
  • ICT Media

Product Synopsis



Language Translation Software: - Markets Reach $123.1 Billion By 2019



LEXINGTON, Massachusetts (May 14, 2013) - WinterGreen Research announces that it has published a new study Language Translation Software : Market Shares, Strategy, and Forecasts, Worldwide, 2013 to 2019. The 2013 study has 437 pages, 122 tables and figures. Worldwide markets are poised to achieve continuing growth as the language translation software systems are put in place to support mobile end point information collections that are localized.



Language translation software market driving forces are related to the Internet usefulness to people in every locality. Smart phones are the latest market driver for software language translation. Every enterprise has to make its web sites user friendly in every locality in which it has a market.



Globally integrated enterprises generally have a presence in from 80 to 170 countries. Localization is equivalent to translation. People then access these web sites and buy from the sites using their smart phones. The Samsung Galaxy S IV can translate several languages in real time. It has the ability to translate off a piece of paper from the camera. Cloud business solutions, social media, and platform systems of engagement represent major IT market shifts. The lines of business are taking over from the IT departments. Systems of engagement leverage the apps market segment that is defined by the line of business more often than by IT. A key cloud computing segment relates to development of apps for every industry. Visual feature and discovery decision tablets permit decision making. Visual decision making components can be exported.

Language translation is used in big data to mine the social media information for comments about products and companies. This data can be used for marketing decision making. Language translation is needed to achieve use of discovery features A trapped decision discovery feature is not too useful. What the systems of engagement seek to do is to capture institutional knowledge, social media knowledge and make it accessible to a broader group of people. Solutions are global. They are based on language translation that makes apps useful globally.



Apps have support for mobile devices. Cloud providers are able to develop custom mobile applications that include toolkits and accelerated systems with common functions that are part of process delivery. Buttons, cameras, geo specific features are available in the apps. It is possible to build composite solutions from within the cloud. Cloud mobile solutions tools mean users can build mobile composite applications that span two platforms.

The brand support provided by the Lionbridge platform is compelling. The ability to support large web-architected brand projects depends on a language platform. Lionbridge has 52,000 individual client translation memories and 14,000 individual translators serving more than 700 clients. These people are supported by the software brand platform.



The company continues to improve the grid architecture of this platform to enable 2,000 concurrent users with 99.9% uptime. Freeway™ is Lionbridge’s free, web-based translation management platform.



Lionbridge provides the world's leading companies with localization solutions for their software, product documentation, marketing materials, training content and web sites to ensure a consistent user experience for their global customers. Localization is a complex process involving many steps all of which are needed to keep a brand intact as it is rolled out to 177 countries with web sites that are all localized to have appeal to the local people:



Hybrid MT systems combine statistical and rules based translation to achieve a degree of accuracy not achievable by either system alone. Hybrid MT systems represent a major shift in language translation markets. It initiates the ability to combine two entirely different ways of achieving machine translation. The two together deliver a level of accuracy that is to be desired.



Statistical MT systems apply statistical techniques to language data. They learn from text alignment. Rules based systems use in depth grammatical rules to achieve knowledge. Linguistic rules are applied to words and phrases for translation based on an in-depth knowledge of the language. MT takes into account the grammatical structure of each language and uses contextual rules to select among multiple meanings. Sentences are translated into the target language.



Rule-based machine translation (RBMT) provides more of a human element to the translation because the rules are user-defined based on an understanding of the target language. The rules can be implemented iteratively, creating a way to achieve greater accuracy as the system is used over the years.



SDL, Lionbridge, IBM and other vendors have positioned to provide industry specific product systems. Solutions are based on an in-depth knowledge of the issues and requirements that drive businesses. SDL takes content, communications, and products worldwide. Worldwide Machine Translation markets at $1.6 billion in 2012 are anticipated to grow to $6.9 billion by-2019. Growth is a result of the inexorable trend toward outreach to the entire world by every enterprise. As the enterprises achieve a global presence in 177 countries, they need automated software translation to achieve a global footprint and achieve localization in the places they expect to do business.


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