Anbukkarasi Sampath


Findings of the Shared Task on Emotion Analysis in Tamil
Anbukkarasi Sampath | Thenmozhi Durairaj | Bharathi Raja Chakravarthi | Ruba Priyadharshini | Subalalitha Cn | Kogilavani Shanmugavadivel | Sajeetha Thavareesan | Sathiyaraj Thangasamy | Parameswari Krishnamurthy | Adeep Hande | Sean Benhur | Kishore Ponnusamy | Santhiya Pandiyan
Proceedings of the Second Workshop on Speech and Language Technologies for Dravidian Languages

This paper presents the overview of the shared task on emotional analysis in Tamil. The result of the shared task is presented at the workshop. This paper presents the dataset used in the shared task, task description, and the methodology used by the participants and the evaluation results of the submission. This task is organized as two Tasks. Task A is carried with 11 emotions annotated data for social media comments in Tamil and Task B is organized with 31 fine-grained emotion annotated data for social media comments in Tamil. For conducting experiments, training and development datasets were provided to the participants and results are evaluated for the unseen data. Totally we have received around 24 submissions from 13 teams. For evaluating the models, Precision, Recall, micro average metrics are used.


Attentive fine-tuning of Transformers for Translation of low-resourced languages @LoResMT 2021
Karthik Puranik | Adeep Hande | Ruba Priyadharshini | Thenmozi Durairaj | Anbukkarasi Sampath | Kingston Pal Thamburaj | Bharathi Raja Chakravarthi
Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021)

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 focuses on getting exceptional translations for rather low-resourced languages like Irish and Marathi. We fine-tune IndicTrans, a pretrained multilingual NMT model for English→Marathi, using external parallel corpus as input for additional training. We have used a pretrained Helsinki-NLP Opus MT English⇔Irish model for the latter language pair. Our approaches yield relatively promising results on the BLEU metrics. Under the team name IIITT, our systems ranked 1, 1, and 2 in English→Marathi, Irish→English, and English→Irish respectively. The codes for our systems are published1 .