Automatic Speech Recognition
NeMo
Safetensors
PyTorch
parakeet_tdt
speech
audio
Transducer
TDT
FastConformer
Conformer
NeMo
hf-asr-leaderboard
Transformers
Eval Results (legacy)
Eval Results
Instructions to use nvidia/parakeet-tdt-0.6b-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/parakeet-tdt-0.6b-v3 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("nvidia/parakeet-tdt-0.6b-v3") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Word boosting
#3
by stefanr123 - opened
Can this model easily be set up to boost certain words?
I noted https://github.com/NVIDIA/NeMo/blob/dcd27ffbaa2ba60e93b8e682e8b033e2382c07c1/docs/source/asr/asr_customization/word_boosting.rst#L4 but a) it's not clear if this applies here and b) it doesn't seem particularly trivial to set up. (As in it's not a simple param you can pass to the invocation of the model).
The word boosting above applies only to CTC decoder models, which this model does not (uses TDT decoder).
Since newer NeMo releases, word boosting is available for TDT models: https://github.com/NVIDIA-NeMo/NeMo/pull/14277
This feature has been introduced in the 2.5.0 release: https://github.com/NVIDIA-NeMo/NeMo/releases/tag/v2.5.0