---
license: cc-by-4.0
language: [en]
pretty_name: CD-ADD
task_categories: [audio-classification]
size_categories: [10K<n<100K]
configs:
  - config_name: default
    data_files:
      - {split: test, path: "data/test-*.parquet"}
tags:
  - anti-spoofing
  - audio-deepfake-detection
  - speech
  - benchmark
  - arena-ready
paperswithcode_id:
arxiv:
  - "2404.04904"
---

# CD-ADD

Benchmark-ready packaging of **CD-ADD** (Cross-Domain Audio Deepfake Detection) for
speech anti-spoofing / synthetic-voice detection.

## Overview

CD-ADD pairs genuine speech with deepfakes produced by five advanced zero-shot
text-to-speech systems (OpenVoice, VALL-E, WhisperSpeech, YourTTS, Seamless). This
repo packages the **LibriTTS `test-clean`** subset together with **all TED talks**
from CD-ADD into a single dataset. The task is binary classification: **bonafide**
(genuine human speech) vs. **spoof** (zero-shot-TTS synthesized speech). Source
paper: https://arxiv.org/abs/2404.04904.

## License & redistribution

Redistributed under the **Creative Commons Attribution 4.0 International (CC BY 4.0)**
license; the full text is in `LICENSE.txt`. Audio is the original 16 kHz mono signal
losslessly re-encoded to FLAC (bit-exact samples); each `real` clip is labelled
bonafide and every TTS-generated clip is labelled spoof.

## Schema

| Field | Type | Description |
|---|---|---|
| path  | string | Source-relative path, unique within the dataset (e.g. `dataset_LibriTTS/test-clean/2300/131720/2300_131720_000002_000001/valle.wav`). |
| audio | Audio(16kHz mono) | Embedded 16 kHz mono audio. |
| label | ClassLabel[bonafide, spoof] | Index 0 = bonafide, 1 = spoof. |
| notes | string (JSON) | Contains a unique `utterance_id`, plus `source` (`libritts`/`ted`), `system` (`real`/`openvoice`/`valle`/`whisperSpeech`/`yourTTS`/`seamless`), `speaker_id`, and `transcript` when available. |

## Quick Start

```python
from datasets import load_dataset
ds = load_dataset("SpeechAntiSpoofingBenchmarks/CD-ADD", split="test")
```

## Stats

| n_total | n_bonafide | n_spoof | total duration |
|---|---|---|---|
| 20,786 | 3,661 | 17,125 | ~58.4 h |

## Source provenance

Built from the CD-ADD release (LibriTTS `test-clean` + all TED talks). Each source
utterance directory contributes one `real.wav` (bonafide) and up to five
zero-shot-TTS spoofs. LibriTTS `dev-clean` / `train-clean-100` are excluded. Every
decodable clip is included; clips that fail to decode via `soundfile` are dropped
(none were dropped in this build).

## Evaluation

See `eval.yaml` and `submissions/README.md`. Primary metric: **EER (%)**, lower is
better.

## Citation

**Original paper**: https://arxiv.org/abs/2404.04904

```bibtex
@article{li2024crossdomain,
  title   = {Cross-Domain Audio Deepfake Detection: Dataset and Analysis},
  author  = {Li, Yuang and Zhang, Min and Ren, Mengxin and Ma, Miaomiao and
             Wei, Daimeng and Yang, Hao},
  journal = {arXiv preprint arXiv:2404.04904},
  year    = {2024}
}
```

## Maintainer

SpeechAntiSpoofingBenchmarks — contact k.n.borodin@mtuci.ru