{"ID":2849592,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.23252","arxiv_id":"2510.23252","title":"Are ASR foundation models generalized enough to capture features of regional dialects for low-resource languages?","abstract":"Conventional research on speech recognition modeling relies on the canonical form for most low-resource languages while automatic speech recognition (ASR) for regional dialects is treated as a fine-tuning task. To investigate the effects of dialectal variations on ASR we develop a 78-hour annotated Bengali Speech-to-Text (STT) corpus named Ben-10. Investigation from linguistic and data-driven perspectives shows that speech foundation models struggle heavily in regional dialect ASR, both in zero-shot and fine-tuned settings. We observe that all deep learning methods struggle to model speech data under dialectal variations but dialect specific model training alleviates the issue. Our dataset also serves as a out of-distribution (OOD) resource for ASR modeling under constrained resources in ASR algorithms. The dataset and code developed for this project are publicly available","short_abstract":"Conventional research on speech recognition modeling relies on the canonical form for most low-resource languages while automatic speech recognition (ASR) for regional dialects is treated as a fine-tuning task. To investigate the effects of dialectal variations on ASR we develop a 78-hour annotated Bengali Speech-to-Te...","url_abs":"https://arxiv.org/abs/2510.23252","url_pdf":"https://arxiv.org/pdf/2510.23252v2","authors":"[\"Tawsif Tashwar Dipto\",\"Azmol Hossain\",\"Rubayet Sabbir Faruque\",\"Md. Rezuwan Hassan\",\"Kanij Fatema\",\"Tanmoy Shome\",\"Ruwad Naswan\",\"Md. Foriduzzaman Zihad\",\"Mohaymen Ul Anam\",\"Nazia Tasnim\",\"Hasan Mahmud\",\"Md Kamrul Hasan\",\"Md. Mehedi Hasan Shawon\",\"Farig Sadeque\",\"Tahsin Reasat\"]","published":"2025-10-27T12:14:52Z","proceeding":"cs.CL","tasks":"[\"cs.CL\"]","methods":"[]","has_code":false}