bengaliAI/Ben-10
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How to use bengaliAI/tugstugi_bengaliai-regional-asr_whisper-medium with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="bengaliAI/tugstugi_bengaliai-regional-asr_whisper-medium") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("bengaliAI/tugstugi_bengaliai-regional-asr_whisper-medium")
model = AutoModelForSpeechSeq2Seq.from_pretrained("bengaliAI/tugstugi_bengaliai-regional-asr_whisper-medium", device_map="auto")This Whisper ASR model was trained on regional Bengali speech data with 10 dialects from the Ben-10 dataset.
Paper: Are ASR foundation models generalized enough to capture features of regional dialects for low-resource languages? (IJCNLP-AACL 2025)
Code: BengaliAI/reg-speech-aacl (training config in finetuning/)
Leaderboard: Ben-10 Regional ASR Leaderboard
Inference Space hosted at https://huggingface.co/spaces/bengaliAI/regional_bengali-asr_tugstugi_whisper-medium
@inproceedings{dipto-etal-2025-asr,
title = "Are {ASR} foundation models generalized enough to capture features of regional dialects for low-resource languages?",
author = "Dipto, Tawsif Tashwar and
Hossain, Azmol and
Faruque, Rubayet Sabbir and
Hassan, Md. Rezuwan and
Fatema, Kanij and
Shome, Tanmoy and
Naswan, Ruwad and
Zihad, Md. Foriduzzaman and
Anam, Mohaymen Ul and
Tasnim, Nazia and
Mahmud, Hasan and
Hasan, Md Kamrul and
Shawon, Md. Mehedi Hasan and
Sadeque, Farig and
Reasat, Tahsin",
booktitle = "Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics",
month = dec,
year = "2025",
address = "Mumbai, India",
publisher = "The Asian Federation of Natural Language Processing and The Association for Computational Linguistics",
url = "https://aclanthology.org/2025.ijcnlp-short.17/",
doi = "10.18653/v1/2025.ijcnlp-short.17",
pages = "178--188",
}