{"id":167879,"date":"2014-10-01T00:00:00","date_gmt":"2014-10-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/word-level-language-identification-using-crf-code-switching-shared-task-report-of-msr-india-system\/"},"modified":"2018-10-16T19:59:50","modified_gmt":"2018-10-17T02:59:50","slug":"word-level-language-identification-using-crf-code-switching-shared-task-report-of-msr-india-system","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/word-level-language-identification-using-crf-code-switching-shared-task-report-of-msr-india-system\/","title":{"rendered":"Word-Level Language Identification Using CRF: Code-Switching Shared Task Report of MSR India System"},"content":{"rendered":"<div class=\"asset-content\">\n<p>We describe a CRF based system for word-level language identification of code-mixed text. Our method uses lexical, contextual, character n-gram, and special character features, and therefore, can easily be replicated across languages. Its performance is benchmarked against the test sets provided by the shared task on code-mixing (Solorio et al., 2014) for four language pairs, namely, English-Spanish (En-Es), English-Nepali (En-Ne),English-Mandarin (En-Cn), and Standard Arabic-Arabic (Ar-Ar) Dialects. The experimental results show a consistent performance across the language pairs.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We describe a CRF based system for word-level language identification of code-mixed text. Our method uses lexical, contextual, character n-gram, and special character features, and therefore, can easily be replicated across languages. Its performance is benchmarked against the test sets provided by the shared task on code-mixing (Solorio et al., 2014) for four language pairs, [&hellip;]<\/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":[13545],"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-167879","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-language-technologies","msr-locale-en_us"],"msr_publishername":"Association for Computational Linguistics","msr_edition":"Proceedings of the First Workshop on Computational Approaches to Code 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