{"id":471423,"date":"2018-03-05T11:58:41","date_gmt":"2018-03-05T19:58:41","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=471423"},"modified":"2018-10-16T22:28:55","modified_gmt":"2018-10-17T05:28:55","slug":"tips-translingual-information-processing-system","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/tips-translingual-information-processing-system\/","title":{"rendered":"TIPS: A Translingual Information Processing System"},"content":{"rendered":"

Searching online information is increasingly a daily activity for many people. The multilinguality of online content is also increasing (e.g. the proportion of English web users, which has been decreasing as a fraction the increasing population of web users, dipped below 50% in the summer of 2001). To improve the ability of an English speaker to search mutlilingual content, we built a system that supports cross-lingual search of an Arabic newswire collection and provides on demand translation of Arabic web pages into English. The cross-lingual search engine supports a fast search capability (sub-second response for typical queries) and achieves state-of-the-art performance in the high precision region of the result list. The on demand statistical machine translation uses the Direct Translation model along with a novel statistical Arabic Morphological Analyzer to yield state-of-the-art translation quality. The on demand SMT uses an efficient dynamic programming decoder that achieves reasonable speed for translating web documents.<\/p>\n","protected":false},"excerpt":{"rendered":"

Searching online information is increasingly a daily activity for many people. The multilinguality of online content is also increasing (e.g. the proportion of English web users, which has been decreasing as a fraction the increasing population of web users, dipped below 50% in the summer of 2001). To improve the ability of an English speaker […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-471423","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"","msr_edition":"HLT-NAACL 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