The George Washington University System for the Code-Switching Workshop Shared Task 2016
نویسندگان
چکیده
We describe our work in the EMNLP 2016 second code-switching shared task; a generic language independent framework for linguistic code switch point detection (LCSPD). The system uses characters level 5-grams and word level unigram language models to train a conditional random fields (CRF) model for classifying input words into various languages. We participated in the Modern Standard Arabic (MSA)-dialectal Arabic (DA) and SpanishEnglish tracks, obtaining a weighted average F-scores of 0.83 and 0.91 on MSA-DA and EN-SP respectively.
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