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RVCBench

RVCBench is a benchmark dataset for studying robustness in voice cloning and related audio generation pipelines.

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
  • 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.

Paper

This dataset is introduced in: RVCBench: Benchmarking the Robustness of Voice Cloning Across Modern Audio Generation Models
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