POS Tagging of English-Hindi Code-Mixed Social Media Content | Zendy

Yogarshi Vyas | Zendy; Spandana Gella | Zendy; Jatin Sharma | Zendy; Kalika Bali | Zendy; Monojit Choudhury | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

POS Tagging of English-Hindi Code-Mixed Social Media Content

Author(s) -

Yogarshi Vyas,

Spandana Gella,

Jatin Sharma,

Kalika Bali,

Monojit Choudhury

Publication year - 2014

Language(s) - English

Resource type - Conference proceedings

DOI - 10.3115/v1/d14-1105

Subject(s) - transliteration , hindi , computer science , spelling , natural language processing , artificial intelligence , social media , language identification , grammar , normalization (sociology) , named entity , world wide web , linguistics , natural language , philosophy , sociology , anthropology

Code-mixing is frequently observed in user generated content on social media, especially from multilingual users. The linguistic complexity of such content is compounded by presence of spelling variations, transliteration and non-adherance to formal grammar. We describe our initial efforts to create a multi-level annotated corpus of Hindi-English codemixed text collated from Facebook forums, and explore language identification, back-transliteration, normalization and POS tagging of this data. Our results show that language identification and transliteration for Hindi are two major challenges that impact POS tagging accuracy.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research