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README.md

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+---
+license: cc-by-4.0
+language:
+- te
+- hi
+- ta
+task_categories:
+- text-to-speech
+- audio-classification
+tags:
+- accent-evaluation
+- phoneme-probe
+- indic
+- retroflex
+- wav2vec2
+- fad
+- psd
+size_categories:
+- 1K<n<10K
+---
+
+# Praxel/psp-native-centroids
+
+Native-speaker reference artefacts for the **PSP** (Phoneme Substitution Profile)
+benchmark for Indic text-to-speech accent evaluation. Companion to the paper
+[PSP: An Interpretable Per-Dimension Accent Benchmark for Indic Text-to-Speech](https://arxiv.org/abs/TBD)
+(Teja, 2026).
+
+This dataset is a **scoring reference**, not a training corpus. It contains
+pre-computed acoustic references extracted from publicly-licensed native-speaker
+speech corpora, used by the [`psp-eval` PyPI package](https://github.com/praxelhq/psp-eval)
+to score TTS outputs on six accent dimensions.
+
+## Contents
+
+Per-language files for Telugu (`te`), Hindi (`hi`), and Tamil (`ta`):
+
+| File | Shape / size | Description |
+|---|---|---|
+| `{lang}_refs.pkl` | `{phoneme: [ndarray (1024,)]}` | Per-phoneme Wav2Vec2-XLS-R layer-9 centroid bags (500-clip bootstrap) |
+| `{lang}_fad_natives.pkl` | `ndarray (1000, 1024)` | Utterance-level XLS-R embeddings for FAD computation |
+| `{lang}_psd_natives.pkl` | `ndarray (500, 5)` | Prosodic feature vectors (F0 mean/std/range, onset-rate, nPVI) for PSD |
+| `{lang}_sanity.json` | small JSON | Held-out native-audio sanity-check scores (§6 paper Signal 5) |
+
+## Provenance
+
+All centroids and reference distributions are derived from:
+- **Telugu**: [IndicTTS](https://www.iitm.ac.in/donlab/tts/) (Telugu subset) — CC-BY-4.0
+- **Hindi**: [Rasa](https://github.com/AI4Bharat/Rasa) (Hindi subset) — CC-BY-4.0
+- **Tamil**: IndicTTS (Tamil subset) — CC-BY-4.0
+
+500 clips per language sampled from the full corpus with seed `1337`. FAD references
+sample 1000 clips from the same pool with the same seed. PSD references sample 500
+clips. Held-out sanity-check clips sample from the same pool with disjoint seed `999`.
+
+Each pickle was produced by `evaluation/psp_bootstrap.py` in the
+[praxelhq/psp-eval repository](https://github.com/praxelhq/psp-eval); see that
+script for the exact extraction pipeline and the alignment-model checkpoints used.
+
+## Usage
+
+```python
+from psp_eval import score_directory
+
+# Centroids auto-download from this repo on first use.
+scores = score_directory("my_tts_outputs/", language="te")
+```
+
+Or load directly in Python:
+
+```python
+import pickle
+from huggingface_hub import hf_hub_download
+
+path = hf_hub_download("Praxel/psp-native-centroids", "te_refs.pkl", repo_type="dataset")
+with open(path, "rb") as f:
+    refs = pickle.load(f)
+# refs: {"ṭ": [np.ndarray (1024,), ...], "ḍ": [...], ...}
+```
+
+## Known caveats
+
+- **Per-phoneme probe noise floor**: native Telugu / Tamil audio registers
+  0.47–0.54 retroflex fidelity when scored against these centroids (not 1.0).
+  This reflects speaker variance between centroid and held-out native corpora,
+  aligner quality, and the strictness of the 0.5 collapse threshold. Interpret
+  per-phoneme scores as **relative rankings across systems**, not absolute
+  distances from a theoretical 1.0 ceiling. See paper §6 Signal 5 for details.
+- **FAD / PSD** do not share this noise floor (native audio correctly scores
+  5–50× lower than commercial-TTS outputs).
+- **Unnormalised Fréchet across mixed-scale PSD dimensions**: nPVI has numeric
+  range ~$10^2$ while log-$F_0$ is ~$10^0$. A z-scored variant is planned for
+  the v2 release.
+
+## Citation
+
+```bibtex
+@misc{teja2026psp,
+  title={{PSP}: An Interpretable Per-Dimension Accent Benchmark for Indic Text-to-Speech},
+  author={Teja, Pushpak},
+  year={2026},
+  eprint={TBD},
+  archivePrefix={arXiv},
+  primaryClass={cs.CL}
+}
+```
+
+## License
+
+CC-BY-4.0 — matching the originating corpus licenses (IndicTTS, Rasa).
+
+## Related
+
+- **Code**: https://github.com/praxelhq/psp-eval (MIT)
+- **PyPI**: `pip install psp-eval`
+- **Paper**: https://arxiv.org/abs/TBD
+
+## Contact
+
+Pushpak Teja — pushpak@praxel.in — [praxel.in](https://praxel.in)

hi_fad_natives.pkl

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hi_psd_natives.pkl

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hi_refs.pkl

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hi_sanity.json

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+{
+  "language": "hi",
+  "n_clips_scored": 50,
+  "retroflex_fidelity_mean": 1.0,
+  "retroflex_collapse_rate": 0.0,
+  "retroflex_n_expected": 103,
+  "retroflex_n_collapsed": 0,
+  "aspiration_fidelity_mean": 1.0,
+  "aspiration_collapse_rate": 0.0,
+  "aspiration_n_expected": 103,
+  "aspiration_n_collapsed": 0,
+  "length_fidelity_mean": 0.3708494186972448,
+  "zha_fidelity_mean": null,
+  "zha_collapse_rate": null,
+  "zha_n_expected": 0,
+  "fad": 43.45411913819434,
+  "fad_mean_norm": 1.692548368729826,
+  "fad_trace_term": 40.58939915770435,
+  "psd": 2.1316744680287396,
+  "psd_mean_norm": 0.9570577451325951
+}

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ta_sanity.json

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+  "psd": 5.566715325207308,
+  "psd_mean_norm": 2.192242106232604
+}

te_fad_natives.pkl

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te_sanity.json

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+  "psd": 4.984875348245255,
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+}