Automatic Speech Recognition
NeMo
speech
audio
fastconformer
mixture-of-experts
multilingual
child-speech
adult-speech
inclusive-ai
Instructions to use TUDelft/inclusive-asr-moe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use TUDelft/inclusive-asr-moe with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("TUDelft/inclusive-asr-moe") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
| Creative Commons Attribution 4.0 International | |
| The model checkpoints in this repository are distributed under the | |
| Creative Commons Attribution 4.0 International License: | |
| https://creativecommons.org/licenses/by/4.0/ | |
| These checkpoints are derived from: | |
| NVIDIA Corporation | |
| nvidia/stt_en_fastconformer_ctc_large | |
| https://huggingface.co/nvidia/stt_en_fastconformer_ctc_large | |
| The original checkpoint is licensed under CC BY 4.0. | |
| Modifications, fine-tuning, sparse Mixture-of-Experts implementation, | |
| experiments, and checkpoint preparation were performed by Amelia Sasin | |
| for the MSc thesis "Mixture-of-Experts Architectures for Inclusive and | |
| Robust Automatic Speech Recognition", TU Delft, 2026. | |
| These derivative models are not endorsed by NVIDIA. | |