Unified Multi-Dialectal Neural Machine Translation for Bangla Using the Dwadash Benchmark Corpus
Neural Machine Translation (NMT) and Large Language Models (LLMs) excel at cross-lingual tasks but often fail to capture intra-lingual morphological variation, marginalizing dialectal speakers. In Bangla, existing translation frameworks commonly rely on Standard Colloquial Bangla (SCB) as an intermediate pivot, which can compound errors and reduce cross-dialectal nuance. To address this gap, we introduce a unified, multi-directional NMT system for direct translation between SCB and eleven regional variants. We first review prior dialectal NLP resources to identify existing technological gaps. As a foundational contribution, we construct and release a large multi-dialect parallel corpus fo...
| Authors | Rakib Ullah, Md. Ruhul Islam, Tanbir Ahmed et al. |
|---|---|
| Primary category | cs.CL |
| Published | 12 August 2026 |
| Last updated at source | 1 September 2026 |
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