Recurrent Neural Network based Part of Speech Tagger for Code Mixed Social Media Text
This paper describes Centre for Development of Advanced Computing's (CDACM) submission to the shared task 'Tool Contest on POS tagging for Code Mixed Indian Social Media (Facebook, Twitter, and Whatsapp) Text' collocated with ICON 2016. The shared task was to predict Part of Speech (POS) tag at word level for a given text. The code mixed text is generated mostly on social media by multilingual users. The presence of the multilingual words, transliterations, and spelling variations make such content linguistically complex. In this paper, we propose an approach to POS tag code mixed social media text using Recurrent Neural Network Language Model (RNN LM) architecture. We submitted the results for Hindi English (hi en) Bengali English (bn en) and Telugu English (te en) code mixed data.
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