{"id":158131,"date":"2009-08-29T00:00:00","date_gmt":"2009-08-29T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/improving-the-quality-of-a-customized-smt-system-using-shared-training-data\/"},"modified":"2018-10-16T20:12:08","modified_gmt":"2018-10-17T03:12:08","slug":"improving-the-quality-of-a-customized-smt-system-using-shared-training-data","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/improving-the-quality-of-a-customized-smt-system-using-shared-training-data\/","title":{"rendered":"Improving the quality of a customized SMT system using shared training data"},"content":{"rendered":"<div class=\"asset-content\">\n<p>The nature of statistical MT systems includes the ability to relatively quickly and easily customize them to a company\u2019s specific domain, by training it on the company\u2019s own parallel data. We are presenting a case study of a customized statistical MT system, which has been trained with an organization\u2019s proprietary data, and show how, and by how much, we can improve the quality of this customized system by using additional training data from trusted sources outside the organization, for instance using data that other companies and organizations have shared in the TAUS Data Association. We will show the process, the criteria, the mechanisms, and the automatic and human evaluation results for each step in the process, enabling the audience to make deliberate choices about how to enhance the composition of training data for their SMT installation.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The nature of statistical MT systems includes the ability to relatively quickly and easily customize them to a company\u2019s specific domain, by training it on the company\u2019s own parallel data. 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