Albany, NY -- (SBWIRE) -- 02/06/2017 -- 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.

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.

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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.

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.

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.

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.

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

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