SBIR Phase II: Software-as-a-Service Customized Machine Translation for Commercial Language Service Providers and Their Clients
National Science Foundation
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Small Business Information
5804 Forbes Avenue, Suite 200, Pittsburgh, PA, 15217
Socially and Economically Disadvantaged:
AbstractThis Small Business Innovation Research Phase-II project develops advanced technology capabilities for constructing and deploying client-adapted automated language translation systems within commercial settings that are used by globalizing enterprises and the language service provider companies (LSPs) that provide translation services to such enterprise clients. The developed technology leverages databases of previously-translated material in order to produce client-adapted high-quality fully-automatic translations for commercial language service providers (LSPs) and their enterprise clients. This approach provides a scalable and less-costly solution for creating and deploying client-specific customized Machine Translation (MT) engines. Once deployed, these customized MT systems expand the capabilities of clients to translate volumes of content that are not feasible to translate using current methods. The broader impact/commercial potential of this project lies in the impact that it will have on the broad commercial translation industry. The technology developed in the project is likely to significantly reduce barriers to wide-spread adoption of MT technology by the broad LSP industry and their enterprise client-base. The 2010 commercial translation market is a $26 billion industry, growing at a healthy pace. Current commercial MT offerings are expensive and too difficult to deploy for most enterprises and service providers. Free web-based translation services serve casual users, but do not meet the quality and security needs of enterprises. The technology developed in this project and the cloud-based delivery model support scalable, easy-to-integrate MT services, which are highly attractive to a broad range of potential clients. This approach will support cost-effective content generation into multiple target languages at a massive scale, a capability that is essential for globalizing US enterprises in order to compete in the information-rich market place of the 21st century.
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