Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Maithili
whisper
maithili
fine-tuned
speech
audio
indian-languages
devanagari
Eval Results (legacy)
Instructions to use rockerritesh/whisper-tiny-maithili with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rockerritesh/whisper-tiny-maithili with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rockerritesh/whisper-tiny-maithili")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("rockerritesh/whisper-tiny-maithili") model = AutoModelForSpeechSeq2Seq.from_pretrained("rockerritesh/whisper-tiny-maithili", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update model card: rename to sumit-maithili-tiny, add proper SYSPIN citation and acknowledgments
Browse files
README.md
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- fine-tuned
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- speech
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- audio
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datasets:
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- rockerritesh/maithili-tts-dataset
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base_model: openai/whisper-tiny
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pipeline_tag: automatic-speech-recognition
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model-index:
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- name:
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results:
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type: automatic-speech-recognition
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name: Word Error Rate
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---
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#
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Fine-tuned [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) for **Maithili** (मैथिली) automatic speech recognition.
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## Dataset
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The model was trained on the **IISc SYSPIN Project Maithili TTS Dataset**
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- **Transcripts:** Devanagari script (Maithili language)
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## Training
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## Citation
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If you use this model, please cite
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```
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}
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```
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- fine-tuned
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- speech
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- audio
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- indian-languages
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- devanagari
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datasets:
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- rockerritesh/maithili-tts-dataset
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base_model: openai/whisper-tiny
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pipeline_tag: automatic-speech-recognition
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model-index:
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- name: sumit-maithili-tiny
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results:
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- task:
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type: automatic-speech-recognition
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name: Word Error Rate
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---
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# sumit-maithili-tiny
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Fine-tuned [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) for **Maithili** (मैथिली) automatic speech recognition.
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## Dataset
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The model was trained on the **IISc SYSPIN Project Maithili TTS Dataset** — studio-recorded speech data released under the [SYSPIN project](https://spiredatasets.iisc.ac.in/syspinCorpus) by the Indian Institute of Science (IISc), Bengaluru.
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| Speaker | Utterances | Duration | Age | Experience |
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| Male (Spk001) | 2,060 | 3h 27m 47s | 43 | 11 Years |
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| Female (Spk001) | 532 | 0h 54m 9s | 30 | 1 Year |
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- **Recording:** Neumann TLM-103 microphone, professional studio, ~40dB SNR
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- **Audio format:** 48kHz, 24-bit, Mono WAV (resampled to 16kHz for training)
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- **Domains:** Agriculture, Books, Finance, Food, Health, India Related, Local Conversation, Politics, Social, Sports, Technology
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- **Transcripts:** Devanagari script (Maithili language)
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- **License:** Audio data is released under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/legalcode.en) by IISc, Bengaluru
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## Training
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## Citation
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If you use this model, please cite:
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```bibtex
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@misc{sumit-maithili-tiny,
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title = {sumit-maithili-tiny: Whisper Tiny Fine-tuned for Maithili ASR},
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author = {Sumit Yadav},
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year = {2026},
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url = {https://huggingface.co/rockerritesh/whisper-tiny-maithili}
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}
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```
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The audio data is from the SYSPIN project. Please also cite:
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```bibtex
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@misc{SYSPIN_S1.0_Corpus,
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title = {SYSPIN_S1.0 Corpus - A TTS Corpus of 900+ hours in nine Indian Languages},
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author = {Abhayjeet Et al.},
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year = {2025}
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}
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```
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## Acknowledgments
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The audio dataset was created under the SYSPIN project by **Indian Institute of Science (IISc), Bengaluru** and is released under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/legalcode.en). We are grateful to the voice artists and the SPIRE Lab, EE Dept., IISc for making this data publicly available.
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Special thanks to the project of German Development Cooperation "FAIR Forward - AI for All" and Bhashini AI Solutions Private Limited for their financial support in developing the TTS corpus.
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**Contact (dataset):** SPIRE Lab, EE Dept., IISc, Bengaluru — contact.syspin@iisc.ac.in
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