Create README.md

README.md

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+---
+language:
+- en
+tags:
+- automatic-speech-recognition
+- speech
+- pathological-speech
+- dysarthria
+- huntingtons-disease
+- nemo
+- parakeet
+- multitask-learning
+- articulation
+license: apache-2.0
+pipeline_tag: automatic-speech-recognition
+library_name: nemo
+base_model: charleslwang/parakeet-tdt-0.6b-HD
+model-index:
+- name: parakeet-tdt-0.6b-HD-articulation
+  results:
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: Huntington Disease clinical speech test set
+      type: private
+    metrics:
+    - type: wer
+      value: 6.44
+      name: WER (%)
+---
+
+# Parakeet-TDT 0.6B HD Articulation
+
+Official checkpoint for the paper **"Towards Robust Automatic Speech Recognition for Huntington Disease."**
+
+## Model description
+
+This model is an articulation-aware variant of **Parakeet-TDT 0.6B HD**, tuned for automatic speech recognition on speech affected by **Huntington disease (HD)**. It extends the HD-adapted base model with auxiliary supervision from articulatory biomarker labels.
+
+## 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 and for analyzing the effect of articulatory supervision on transcription behavior.
+
+## Training
+
+The model was initialized from `charleslwang/parakeet-tdt-0.6b-HD` and further adapted using **parameter-efficient encoder-side adapters** with an auxiliary objective based on articulatory biomarker labels, while keeping the pretrained backbone frozen.
+
+## Evaluation
+
+On the reported HD test set, this model achieved:
+
+- **WER:** 6.44
+- **Substitutions:** 1.94
+- **Deletions:** 3.21
+- **Insertions:** 1.29
+
+## Intended use
+
+This model is intended for:
+
+- research on pathological / atypical speech recognition,
+- benchmarking ASR on Huntington disease speech,
+- studying how articulatory auxiliary supervision reshapes error behavior.
+
+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.
+- Did not outperform the plain HD-adapted model on overall WER.
+- May not generalize to severe out-of-distribution impairment, other languages, or other recording conditions.