This is a Danish state-of-the-art speech recognition model, trained by
Alvenir.
Results of more models and more datasets can be seen in the
model card for Røst-315m.
This is simply the
Whisper Large v.3 model trained on the first release of
CoRaL data.
The model was trained for 30K steps using the configuration from the
CoRaL repository by running:
1
2python src/scripts/finetune_asr_model.py model=whisper-large max_steps=30000 model.learning_rate=1e-5
Note that the dataset used is licensed under a custom license, adapted from OpenRAIL-M, which allows
commercial use with a few restrictions (speech synthesis and biometric identification).
See
license.
The CoRal project is funded by the
Danish Innovation
Fund and consists of the following partners:
We would like specifically thank Dan Saattrup Nielsen, Alexandra Institute for (among other things) the repository work and Simon Leminen Madsen, Alexandra Institute for modelling work.
