{"id":468891,"date":"2018-02-23T08:46:23","date_gmt":"2018-02-23T16:46:23","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=468891"},"modified":"2018-10-16T22:29:39","modified_gmt":"2018-10-17T05:29:39","slug":"symgiza-tool-parallel-computation-symmetrized-word-alignment-models","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/symgiza-tool-parallel-computation-symmetrized-word-alignment-models\/","title":{"rendered":"SyMGiza++: A tool for parallel computation of symmetrized word alignment models"},"content":{"rendered":"

SyMGiza++ – a tool that computes symmetric word alignment models with the capability to take advantage of multi-processor systems – is presented. A series of fairly simple modifications to the original IBM\/Giza++ word alignment models allows to update the symmetrized models between each iteration of the original training algorithms. We achieve a relative alignment quality improvement of more than 17% compared to Giza++ and MGiza++ on the standard Canadian Hansards task, while maintaining the speed improvements provided by MGiza++’s capability of parallel computations.<\/p>\n","protected":false},"excerpt":{"rendered":"

SyMGiza++ – a tool that computes symmetric word alignment models with the capability to take advantage of multi-processor systems – is presented. A series of fairly simple modifications to the original IBM\/Giza++ word alignment models allows to update the symmetrized models between each iteration of the original training algorithms. We achieve a relative alignment quality […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","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-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-468891","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of the 2010 International Multiconference on Computer Science and Information Technology 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