Abstract
This overview paper presents the findings of the two shared tasks organized as part of the 1st Workshop on Benchmarks, Harmonization, Annotation, and Standardization for Human-Centric AI in Indian Languages (BHASHA) co-located with IJCNLP-AACL 2025. The shared tasks are: (1) Indic Grammar Error Correction (IndicGEC) and (2) Indic Word Grouping (IndicWG). For GEC, participants were tasked with producing grammatically correct sentences based on given input sentences in five Indian languages. For WG, participants were required to generate a word-grouped variant of a provided sentence in Hindi. The evaluation metric used for GEC was GLEU, while Exact Matching was employed for WG. A total of 14 teams participated in the final phase of the Shared Task 1; 2 teams participated in the final phase of Shared Task 2. The maximum GLEU scores obtained for Hindi, Bangla, Telugu, Tamil and Malayalam languages are respectively 85.69, 95.79, 88.17, 91.57 and 96.02 for the IndicGEC shared task. The highest exact matching score obtained for IndicWG shared task is 45.13%.
Hrishikesh Terdalkar
Assistant Professor
My research lies at the intersection of Computational Linguistics, Natural Language Processing, and Knowledge Graphs with a particular emphasis on low-resource languages such as Sanskrit and other Indian languages. My recent work has focused on building datasets, models, benchmarks, and evaluation frameworks grounded in linguistic structure. My interests also include Artificial Intelligence, Information Retrieval, Human-Computer Interaction, and Data Mining.