--- license: mit tags: - text-to-articulation - articulatory-kinematics - speech-synthesis - sparc language: - en datasets: - mythicinfinity/libritts_r --- # STArK (large) — Interspeech 2026 paper checkpoint This is the checkpoint used for the results reported in **STArK: Towards Synthesizing Articulatory Kinematics from Text** (Xavier Yin, Carlos Busso, Interspeech 2026). - Code: https://github.com/Lab-MSP/STArK - Paper (temporary link): https://lab-msp.com/MSP/publications/Yin_2026.pdf - Project page: https://lab-msp.github.io/STArK/ ## Which checkpoint is this? | File / revision | Training step | Notes | |---|---|---| | `checkpoint.ckpt` on `main` (tag `paper-step-32k`) | 32,000 | **Paper checkpoint.** `model=large_model train=train_large`, LibriTTS-R `train-clean-100`. | | `checkpoint.ckpt` at tag `step-100k` | 100,000 | Longer, separate training run. Published here from 2026-08-23 to 2026-11-05. It does **not** match the paper's reported results. | `main` served the 100k-step checkpoint until 2026-11-05. If you downloaded this model before that date, you have the 100k-step model, not the paper model. Re-download to get the paper checkpoint. SHA-256 of the paper checkpoint (`checkpoint.ckpt` on `main`): `1a704e045295e90c182001543b7fe0e2cb1fcb6fc9519a932e2bcb2da2dac5f3` ## Usage ```bash git clone https://github.com/Lab-MSP/STArK && cd STArK && uv sync python scripts/stark_cli.py synthesize "Hello, this is a test." \ --reference-audio my_voice.wav --output out.wav ``` The CLI downloads `checkpoint.ckpt` from this repo's `main` branch by default. To load the 100k-step run instead: ```python from huggingface_hub import hf_hub_download path = hf_hub_download("Lab-MSP/stark-large", "checkpoint.ckpt", revision="step-100k") ``` Then pass `--checkpoint ` to `stark_cli.py`. ## Citation ```bibtex @inproceedings{yin2026stark, title = {{STArK}: Towards Synthesizing Articulatory Kinematics from Text}, author = {Yin, Xavier and Busso, Carlos}, booktitle = {Proc. Interspeech 2026}, year = {2026} } ``` STArK resynthesizes speech with the SPARC vocoder; please also cite SPARC (Cho et al., "Coding Speech through Vocal Tract Kinematics", IEEE JSTSP 2024).