Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation or interactive translation) is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one natural language to another.
In the 80s and 90s MT software was rule-based, but in the 2000s statistical analysis and the re-emergence of neural networking and more advanced machine learning techniques have proved to be far more successful.
Now more commonly known as machine translation (MT), refers to the the use of software to translate text or speech from one language to another. In the 80s and 90s MT software was rule-based, but in the 2000s statistical analysis and the re-emergence of neural networking and more advanced machine learning techniques have proved to be far more successful.
Language localization (from Latin locus and the English term locale, “a place where something happens or is set”) is the second phase of a larger process of product translation and cultural adaptation (for specific countries, regions or groups) to account for differences in distinct markets, a process known as internationalization and localization.
W3C announced new work to make it easier for people to create Web content in the world’s languages. The lack of standards for exchanging information about translations is estimated to cost the industry as much as 20% more in translation costs, amounting to billions of dollars. In addition, barriers to distributing content in more than one language mean lost business. Multinational companies often need to translate Web content into dozens of languages simultaneously, and public bodies from Europe and India typically must communicate with citizens in many languages. As the Web becomes more diverse linguistically, translation demands will continue to grow.
The MultilingualWeb–LT (Language Technology) Working Group will develop standard ways to support the (automatic and manual) translation and adaptation of Web content to local needs, from its creation to its delivery to end users. The MultilingualWeb-LT Working Group receives funding from the European Commission (project name LT-Web) through the Seventh Framework Programme (FP7).
Astoria Software and Translations.com have aligned in order to create a single solution for managing and localizing XML content. This joint development initiative, Translation-Enabled Content Management, represents the service-level integration of Astoria On-Demand and Translations.com’s GlobalLink Localization Suite. Translation-Enabled Content Management will provide global organizations with a way to bring product information to market simultaneously in any locale and language. Key components of the Translation-Enabled Content Management initiative include: seamless integration of GlobalLink Project Director functionality embedded in the Astoria On-Demand user-interface; allows Astoria On-Demand users to work directly with Translations.com’s ISO-certified linguistic team or use other internal/external translation resources; centralized project tracking, business process automation and reporting for all localization projects across all vendors; server-based translation memory integration capabilities via GlobalLink Server; Secure Socket Layer (SSL) encryption of all data travelling to and from the end-user’s desktop, as well as data travelling between Astoria On-Demand and GlobalLink; a Service Oriented Architecture that IT can integrate into their SOA Governance and Deployment policy frameworks; unified solution for the creation, management, localization and production of XML-based documentation; and, data and Service hosting in Tier 1 data centers that comply with SAS 70 Type II guidelines for physical and logical security and resiliency. http://www.astoriasoftware.com/ http://www.translations.com/