56 citations · 107 across the 10 of their papers we have counts for
10 papers
TamilEmo: Finegrained Emotion Detection Dataset for Tamil
Charangan Vasantharajan, Sean Benhur, Prasanna Kumar Kumarasen +8
Emotional Analysis from textual input has been considered both a challenging and interesting task in Natural Language Processing. However, due to the lack of datasets in low-resour…
Hypers at ComMA@ICON: Modelling Aggressiveness, Gender Bias and Communal Bias Identification
Sean Benhur, Roshan Nayak, Kanchana Sivanraju +4
Due to the exponentially increasing reach of social media, it is essential to focus on its negative aspects as it can potentially divide society and incite people into violence. In…
Developing Successful Shared Tasks on Offensive Language Identification for Dravidian Languages
Bharathi Raja Chakravarthi, Dhivya Chinnappa, Ruba Priyadharshini +7
With the fast growth of mobile computing and Web technologies, offensive language has become more prevalent on social networking platforms. Since offensive language identification…
Dataset for Identification of Homophobia and Transophobia in Multilingual YouTube Comments
Bharathi Raja Chakravarthi, Ruba Priyadharshini, Rahul Ponnusamy +6
The increased proliferation of abusive content on social media platforms has a negative impact on online users. The dread, dislike, discomfort, or mistrust of lesbian, gay, transge…
Attentive fine-tuning of Transformers for Translation of low-resourced languages @LoResMT 2021
Karthik Puranik, Adeep Hande, Ruba Priyadharshini +4
This paper reports the Machine Translation (MT) systems submitted by the IIITT team for the English->Marathi and English->Irish language pairs LoResMT 2021 shared task. The task fo…
Offensive Language Identification in Low-resourced Code-mixed Dravidian languages using Pseudo-labeling
Adeep Hande, Karthik Puranik, Konthala Yasaswini +6
Social media has effectively become the prime hub of communication and digital marketing. As these platforms enable the free manifestation of thoughts and facts in text, images and…