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README.md

@@ -1,50 +1,77 @@
 ---
+pretty_name: RVCBench
+license: cc0-1.0
+language:
+  - en
+  - zh
+  - fr
+task_categories:
+  - text-to-speech
+  - automatic-speech-recognition
+tags:
+  - voice-cloning
+  - text-to-speech
+  - speaker-privacy
+  - audio-protection
+  - adversarial-audio
+  - audio-deepfake
+  - speaker-verification
+  - speech-synthesis
+  - robustness
+  - benchmark
+  - zero-shot-voice-cloning
 configs:
   - config_name: AISHELL1_dev
     data_files:
-      - split: test
+      - split: default
         path: AISHELL1_dev/metadata.parquet
   - config_name: Background_noise
     data_files:
-      - split: test
+      - split: default
         path: Background_noise/metadata.parquet
   - config_name: Bilingual_uedin
     data_files:
-      - split: test
+      - split: default
         path: Bilingual_uedin/metadata.parquet
   - config_name: CommonVoiceFR_dev
     data_files:
-      - split: test
+      - split: default
         path: CommonVoiceFR_dev/metadata.parquet
   - config_name: Libritts
     data_files:
-      - split: test
+      - split: default
         path: Libritts/metadata.parquet
   - config_name: Long_context
     data_files:
-      - split: test
+      - split: default
         path: Long_context/metadata.parquet
   - config_name: Multispeaker_libri
     data_files:
-      - split: test
+      - split: default
         path: Multispeaker_libri/metadata.parquet
   - config_name: VCTK
     data_files:
-      - split: test
+      - split: default
         path: VCTK/metadata.parquet
   - config_name: robotcall
     data_files:
-      - split: test
+      - split: default
         path: robotcall/metadata.parquet
   - config_name: vctk_text_robust
     data_files:
-      - split: test
+      - split: default
         path: vctk_text_robust/metadata.parquet
 ---
 
 # RVCBench
 
-RVCBench is a benchmark dataset for studying robustness in voice cloning and related audio generation pipelines.
+RVCBench is a benchmark dataset for studying robustness in voice cloning, text-to-speech, speaker privacy, audio protection, adversarial audio perturbations, and related audio generation pipelines.
+
+Dataset page: https://huggingface.co/datasets/Nanboy/RVCBench
+Code repository: https://github.com/Nanboy-Ronan/RVCBench
+Paper: https://arxiv.org/abs/2602.00443
+
+RVCBench is designed for evaluating how modern voice cloning (VC), TTS, and audio generation systems behave under clean prompts, protected prompts, and denoised protected prompts. It supports research on audio deepfake robustness, anti-spoofing, speaker verification resilience, privacy-preserving speech generation, and standardized benchmark evaluation.
 
 Each subset is exposed as its own Hugging Face dataset configuration. Most subsets contain:
 
@@ -62,7 +89,7 @@ The canonical metadata stores one row per benchmark pair with columns such as:
 - `target_language`
 - `pair_id`
 - `dataset_name`
-- `split`
+- `data_split`
 
 When available, training-oriented annotations are also preserved:
 
@@ -84,12 +111,29 @@ Some subsets include additional task-specific metadata, for example `spam_type`
 - `robotcall`
 - `vctk_text_robust`
 
+## Intended Use
+
+Use this dataset with the RVCBench codebase to run reproducible voice cloning robustness experiments across source audio, protected audio, denoised audio, and generated audio. Typical tasks include:
+
+- benchmarking zero-shot voice cloning and TTS models;
+- comparing audio protection methods such as SafeSpeech, Enkidu, EM, AntiFake, and Gaussian noise;
+- measuring speaker similarity, intelligibility, perceptual quality, word error rate, and runtime;
+- studying speaker privacy and audio deepfake robustness under adversarial perturbations.
+
+## Citation
+
+If you use RVCBench in your research, please cite:
+
+```bibtex
+@article{liao2026rvcbench,
+  title   = {RVCBench: Benchmarking the Robustness of Voice Cloning Across Modern Audio Generation Models},
+  author  = {Liao, Xinting and Jin, Ruinan and Yu, Hanlin and Pandya, Deval and Li, Xiaoxiao},
+  journal = {arXiv preprint arXiv:2602.00443},
+  year    = {2026}
+}
+```
+
 ## Notes
 
 - The `compression` directory is intentionally excluded from this dataset release.
 - This repository is organized for direct browsing in the Hugging Face dataset viewer.
-
-## Paper
-
-This dataset is introduced in:
-[RVCBench: Benchmarking the Robustness of Voice Cloning Across Modern Audio Generation Models](https://arxiv.org/abs/2602.00443)

README_HF_DATASET.md

@@ -0,0 +1,92 @@
+---
+configs:
+  - config_name: AISHELL1_dev
+    data_files:
+      - split: default
+        path: AISHELL1_dev/metadata.parquet
+  - config_name: Background_noise
+    data_files:
+      - split: default
+        path: Background_noise/metadata.parquet
+  - config_name: Bilingual_uedin
+    data_files:
+      - split: default
+        path: Bilingual_uedin/metadata.parquet
+  - config_name: CommonVoiceFR_dev
+    data_files:
+      - split: default
+        path: CommonVoiceFR_dev/metadata.parquet
+  - config_name: Libritts
+    data_files:
+      - split: default
+        path: Libritts/metadata.parquet
+  - config_name: Long_context
+    data_files:
+      - split: default
+        path: Long_context/metadata.parquet
+  - config_name: Multispeaker_libri
+    data_files:
+      - split: default
+        path: Multispeaker_libri/metadata.parquet
+  - config_name: VCTK
+    data_files:
+      - split: default
+        path: VCTK/metadata.parquet
+  - config_name: robotcall
+    data_files:
+      - split: default
+        path: robotcall/metadata.parquet
+  - config_name: vctk_text_robust
+    data_files:
+      - split: default
+        path: vctk_text_robust/metadata.parquet
+---
+
+# RVCBench
+
+RVCBench is a benchmark dataset for studying robustness in voice cloning and related audio generation pipelines.
+
+Dataset page: https://huggingface.co/datasets/Nanboy/RVCBench
+
+Each subset is exposed as its own Hugging Face dataset configuration. Most subsets contain:
+
+- `metadata.parquet`
+- `audios/`
+
+The canonical metadata stores one row per benchmark pair with columns such as:
+
+- `speaker_id`
+- `prompt_file_name`
+- `prompt_text`
+- `prompt_language`
+- `target_file_name`
+- `target_text`
+- `target_language`
+- `pair_id`
+- `dataset_name`
+- `data_split`
+
+When available, training-oriented annotations are also preserved:
+
+- `prompt_phonemes`, `prompt_tone`, `prompt_word2ph`
+- `target_phonemes`, `target_tone`, `target_word2ph`
+
+Some subsets include additional task-specific metadata, for example `spam_type` in `robotcall`.
+
+## Available Configs
+
+- `AISHELL1_dev`
+- `Background_noise`
+- `Bilingual_uedin`
+- `CommonVoiceFR_dev`
+- `Libritts`
+- `Long_context`
+- `Multispeaker_libri`
+- `VCTK`
+- `robotcall`
+- `vctk_text_robust`
+
+## Notes
+
+- The `compression` directory is intentionally excluded from this dataset release.
+- This repository is organized for direct browsing in the Hugging Face dataset viewer.