Parakeet-TDT 0.6B HD

Official checkpoint for the paper "Huntington Disease Automatic Speech Recognition with Biomarker Supervision."

Model description

This model is an HD-adapted version of NVIDIA Parakeet-TDT 0.6B v2, tuned for automatic speech recognition on speech affected by Huntington disease (HD). It is the strongest model in the ParakeetHD suite and serves as the main disease-adapted recognizer in the paper.

What this model does

The model transcribes English read / controlled clinical speech from speakers with Huntington disease and healthy controls. It is intended as a research model for studying robust ASR under hyperkinetic motor-speech disruption.

Training

The model was adapted from nvidia/parakeet-tdt-0.6b-v2 using parameter-efficient encoder-side adapters while keeping the pretrained backbone frozen.

Evaluation

On the reported HD test set, this model achieved:

WER: 4.95
Substitutions: 2.09
Deletions: 1.29
Insertions: 1.57

Intended use

This model is intended for:

research on pathological / atypical speech recognition,
benchmarking ASR on Huntington disease speech,
studying error behavior under hyperkinetic disruption.

It is not intended for clinical diagnosis, treatment decisions, or standalone medical use.

Limitations

Trained and evaluated on a relatively small, high-fidelity clinical corpus.
Primarily reflects controlled / read speech rather than spontaneous conversational speech.
May not generalize to severe out-of-distribution impairment, other languages, or other recording conditions.

Citation

If you use this model, please cite:

@article{wang2026huntington,
  title={Huntington Disease Automatic Speech Recognition with Biomarker Supervision},
  author={Wang, Charles L. and Chen, Cady and Gong, Ziwei and Hirschberg, Julia},
  journal={arXiv preprint arXiv:2603.11168},
  year={2026},
  url={https://arxiv.org/abs/2603.11168}
}