SSN-Nova@LT-EDI 2024: Leveraging Vectorisation Techniques in an Ensemble Approach for Stress Identification in Low-Resource Languages

AbstractThis paper presents our submission for Shared task on Stress Identification in Dravidian Languages: StressIdent LT-EDI@EACL2024. The objective of this task is to identify stress levels in individuals based on their social media content. The system is tasked with analysing posts written in a code-mixed language of Tamil and Telugu and categorising them into two labels: “stressed” or “not stressed.” Our approach aimed to leverage feature extraction and juxtapose the performance of widely used traditional, deep learning and transformer models. Our research highlighted that building a pipeline with traditional classifiers proved to significantly improve their performance (0.98 and 0.93 F1-scores in Telugu and Tamil respectively), surpassing the baseline as well as deep learning and transformer models.