DravidianCodeMix: sentiment analysis and offensive language identification dataset for Dravidian languages in code-mixed text.

This paper describes the development of a multilingual, manually annotated dataset for three under-resourced Dravidian languages generated from social media comments. The dataset was annotated for sentiment analysis and offensive language identification for a total of more than 60,000 YouTube comments. The dataset consists of around 44,000 comments in Tamil-English, around 7000 comments in Kannada-English, and around 20,000 comments in Malayalam-English.

Prevalence and Influencing Risk Factors of Voice Problems in Priests in Kerala.

Objective: Voice problems are commonly reported by professionals in occupations involving a large amount of voice loading. The aim of the present study was to investigate the prevalence of voice problems in Mar Thoma priests and identify possible risk factors responsible for voice problems.

Study Design: This is a cross-sectional study.