no code implementations • 27 Nov 2022 • Neeraja Kirtane, Jeshuren Chelladurai, Balaraman Ravindran, Ashish Tendulkar
Changing data composition is a popular way to address the imbalance in node classification.
no code implementations • 8 Sep 2022 • Neeraja Kirtane, V Manushree, Aditya Kane
Our major contributions in this paper are the construction of a novel corpus to evaluate occupational gender bias in Hindi, quantify this existing bias in these systems using a well-defined metric, and mitigate it by efficiently fine-tuning our model.
Bias Detection Cultural Vocal Bursts Intensity Prediction +1
no code implementations • NAACL (GeBNLP) 2022 • Neeraja Kirtane, Tanvi Anand
While research is being done in English to quantify and mitigate bias, debiasing methods in Indic Languages are either relatively nascent or absent for some Indic languages altogether.
no code implementations • WASSA (ACL) 2022 • Aditya Kane, Shantanu Patankar, Sahil Khose, Neeraja Kirtane
Detecting emotions in languages is important to accomplish a complete interaction between humans and machines.