Year: 2026
Type: conference-paper
Abstract: Regional dialects of Bangla, such as Sylheti and Chittagonian, pose significant challenges for natural language processing due to their low-resource nature and substantial linguistic variation from standard Bangla.In this work, we present a systematic evaluation of eight open-source LLMs for translating fifteen distinct Bangla dialects into standard Bangla.To achieve this comprehensive coverage, we utilize a combination of established benchmarks and a novel dataset curated from an ongoing regional linguistic project.We assess model performance using a multi-metric framework that combines exact-match and error-rate evaluations such as, Averaged BLEU, WER, and CER with embedding-based semantic metrics including BERTScore, METEOR, and COMET.Additionally, we perform a detailed dialect-level linguistic analysis to identify the deep-seated structural, orthographic, and semantic barriers inherent to dialectal translation.Our study highlights the strengths and limitations of current open-source models, provides empirical insights for future dialect-aware fine-tuning, and contributes a reproducible benchmark for the research community.
Institutions: BRAC University, United International University
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7166549334
FWCI:
Cites:
Cited by:
Related to: