Add dataset card

README.md

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+---
+license: cc-by-4.0
+language:
+  - en
+pretty_name: cond-DIM audio samples
+size_categories:
+  - 1K<n<10K
+task_categories:
+  - text-to-speech
+tags:
+  - speech
+  - text-to-speech
+  - zero-shot-tts
+  - voice-cloning
+  - machine-unlearning
+  - speaker-unlearning
+  - cond-dim
+  - evaluation
+---
+
+# cond-DIM — audio samples
+
+Synthesized audio backing the ICASSP 2027 submission **"cond-DIM: One Method, Three
+Conditioning Paths for Host-Independent Speaker Unlearning in Autoregressive Zero-Shot
+TTS."** ~2,450 clips: every backbone, every baseline, and the relearn stress test.
+
+🔇 **Prefer listening in the browser?** → [Live demo Space](https://huggingface.co/spaces/RootAccess4Life/voiceeraser-demo)
+
+## The one thing to listen for
+
+Each speaker appears as a **pair**:
+
+| clip | meaning |
+|---|---|
+| `cB_…` | **baseline** clone — the un-edited model cloning that speaker. This is the voice being copied. |
+| `cE_…` | **edited** clone — the same model, same reference, *after* cond-DIM unlearning. The identity should be gone. |
+| `cRL_…` | **relearn** clone — after a white-box attacker re-finetunes to recover the erased speaker. |
+
+Play `cB` then `cE` for the same speaker: intelligible speech in both, but the voice
+identity should no longer match. `cRL` asks whether an adversary can undo that.
+
+## Filename convention
+
+```
+{cB|cE|cRL}_{speaker}_{sentence}.wav
+```
+
+Speaker ids are VCTK (`p225`, `p272`, …) or LibriTTS (`103`, `118`, …) depending on the
+split; `{sentence}` indexes a fixed sentence bank, so the same index is the same text
+across every directory. TruS-F5 clips carry an extra seed field
+(`cB_s0_p225_0.wav`).
+
+## Directory map
+
+**Main result — cond-DIM on three backbones**
+
+| directory | backbone |
+|---|---|
+| `xtts_clones/` | XTTS-v2 |
+| `tortoise_clones/` | Tortoise-TTS |
+| `indextts_clones/` | IndexTTS-1.5 |
+
+**Stress tests**
+
+| directory | what it shows |
+|---|---|
+| `xtts_relearn_clones/` | white-box relearn attack on XTTS-v2 (`cRL_`) |
+| `sequential/{xtts,tortoise,indextts}_clones/` | sequential opt-out — speakers erased one after another |
+
+**Baselines** (each in `{method}_{backbone}_clones/`)
+
+`additive_gaussian` · `gradient_ascent_to_forget` · `random_reference_substitution` ·
+`task_arithmetic` · `zero_pooled_identity`
+
+**TruS on F5-TTS**
+
+| directory | contents |
+|---|---|
+| `trus_f5_clones/` | TruS-F5 clones (VCTK) |
+| `trus_f5_libritts_clones/` | TruS-F5 clones (LibriTTS) |
+| `trus_f5_frontier/` | α/threshold frontier sweeps (JSON metrics, not audio) |
+
+## Loading
+
+Stream a single clip without cloning the whole set:
+
+```python
+from huggingface_hub import hf_hub_download
+
+p = hf_hub_download(
+    repo_id="RootAccess4Life/voiceeraser-samples",
+    filename="xtts_clones/cE_103_0.wav",
+    repo_type="dataset",
+)
+```
+
+Or grab one backbone:
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download(
+    repo_id="RootAccess4Life/voiceeraser-samples",
+    repo_type="dataset",
+    allow_patterns=["xtts_clones/*"],
+)
+```
+
+## Provenance and licensing
+
+Clips are synthesized by XTTS-v2, Tortoise-TTS, IndexTTS-1.5 and F5-TTS from reference
+audio in **CSTR VCTK-Corpus-0.92** (CC-BY-4.0, [DOI 10.7488/ds/2645](https://doi.org/10.7488/ds/2645))
+and **LibriTTS** (CC-BY-4.0, OpenSLR SLR60). This dataset is released **CC-BY-4.0** to
+match those sources.
+
+The generating models keep their own licenses — notably **XTTS-v2 is non-commercial
+(CPML)**. Those terms constrain the models, not these audio files, but review them before
+building on the pipeline.
+
+## Intended use and limits
+
+Released for **research and demonstration**: verifying the paper's claims by ear, and
+supporting work on speaker unlearning, privacy, and the right to be forgotten in speech
+synthesis.
+
+These are synthetic clones of real speakers, produced to demonstrate *removing* voice
+identity. Do not use them to impersonate anyone, to train or evaluate systems that
+attribute speech to the original speakers, or as evidence any of these people said these
+words — **they did not**. The `cB_` clips in particular are deliberate voice clones and
+should be handled accordingly.
+
+## Related
+
+- 💻 Code: https://github.com/pujariaditya/cond-dim-tts-unlearning
+- 🔇 Live demo: https://huggingface.co/spaces/RootAccess4Life/voiceeraser-demo
+- 📦 Mirrors: [XTTS-v2](https://huggingface.co/RootAccess4Life/voiceeraser-xtts-v2) · [IndexTTS-1.5](https://huggingface.co/RootAccess4Life/voiceeraser-indextts-1.5)
+
+## Citation
+
+```bibtex
+@inproceedings{pujari2027conddim,
+  title     = {cond-DIM: One Method, Three Conditioning Paths for Host-Independent
+               Speaker Unlearning in Autoregressive Zero-Shot TTS},
+  author    = {Pujari, Aditya and Rattani, Ajita},
+  booktitle = {Proceedings of the IEEE International Conference on Acoustics,
+               Speech and Signal Processing (ICASSP)},
+  year      = {2027},
+}
+```