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Language Translation Software: Market Shares, Strategies, And Forecasts, Worldwide 2020

05-15-2017 02:10 PM CET | IT, New Media & Software

Press release from: MarketResearchReports.biz

Language Translation Software: Market Shares, Strategies,

"The Report Language Translation Software: Market Shares, Strategies, and Forecasts, Worldwide, 2014 to 2020 provides information on pricing, market analysis, shares, forecast, and company profiles for key industry participants. - MarketResearchReports.biz"

About Language Translation Software Market

LEXINGTON, Massachusetts (October 31, 2014) – WinterGreen Research announces that it has published a new study Language Translation Software: Market Shares, Strategy, and Forecasts, Worldwide, 2014 to 2020. The 2014 study has 536 pages, 151 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.

Enterprise server has reached a long sought after milestone. With language translation software technology reaching a more mature state, comprehensive solutions are available that have never been available before. Comprehensive solutions combine the best attributes of rule-based and statistical machine translation. These integrated systems are able to meet the full range of translation needs on an enterprise scale.

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Systems are powered by hybrid machine translation (MT) engines. IT enterprise-level machine translation combines rules systems and statistical systems to achieve a hybrid solution. These are a “black-box solution” due to the complexity of the software implementation and resources needed to successful train an engine.

Iterative software releases are evolving. They represent a goal executives want to reach. Iterative software releases allow larger vendors to compete with smaller, more nimble companies by making their feature function packages more robust. Meeting the Iterative software releases challenge depends on achieving an agile software development environment.

Continuous localization represents automation of localization resource bundles. Implementing internationalization depends on best practice systems use at the engineering level and further down the production chain. The largest IT localization are approached by bridging the gap between development and reuse of existing code modules. Products are positioned to address challenges directly.

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The concept of bringing translation management practices to overall software development is significant. Because language translation systems implement such robust content management solutions, a company can leverage its language translation expertise to offer hybrid sophisticated content management systems. These have the prospect of building much broader markets for localization for all software applications.

Language translation software market driving forces relate to localization at all levels of business process. 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 that have been incorporated by language translation software systems. The lines of business have taking over from the IT departments, but with cloud computing there is a transition back to IT.

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

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.

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 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.

Companies Profiled

Market Leaders

Lionbridge
SDL / Trados
Babylon
Microsoft
Systran
Softissimo
IBM
Google
Asia Online
Language Engineering, LLC (LEC)

Market Participants
AlphaCRC
American Translators Association (ATA)
Asia Online
Bablefish
Babylon
The Big Word
Bitext
CallMiner
China Translation Industry
Cloudwords
Duolingo
Globalization and Localization Association (GALA)
Google
Hewlett Packard
IBM
Jonckers
Kilgray
Language Engineering, LLC (LEC)
Lingo24
Lingotek
Lionbridge
Lloyd International Translations
Mission Essential Personnel (MEP)
Moravia
MultiCorpora
Niemanlab.Org
Nuance
OpenAmplify
Pactera Technology / HiSoft
Plunet BusinessManager
ProZ.com
Reverso-Softissimo
RWS Legal Translation
SDL
Star Group
Symbio
Systran
Translations.com
Translators Without Borders
Veveo
Vignette Content Management (VCM)
WorldLingo

Key Topics

Language Translation Software
Language Translation
Machine Language
Hybrid Translation
Software Localization
Language Teams
Key Translation Parameters
Rule-Based Machine
Translation
Statistical Machine
Translation
Rules Based Machine Translation
Linguistic Services
Language Translation Shares
Machine Language
Translation Localization
Translation Localization
Growth
Translation Memory
Systems of Engagement
Mobile End Points
Social Media Apps
Social Cloud
Combined Statistical and
Rules Based Translation
Linguistic Rules
Chinese-English Machine Translation
English-Chinese Machine
Translation
Rule-Based Machine
Translation System
Hybrid Approach
Statistical Post-Editing
Translation Localization

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