| --- |
| license: cc-by-nc-4.0 |
| language: |
| - en |
| - zh |
| pretty_name: SONAR |
| task_categories: [audio-classification] |
| size_categories: [1K<n<10K] |
| configs: |
| - config_name: default |
| data_files: |
| - {split: test, path: "data/test-*.parquet"} |
| tags: |
| - anti-spoofing |
| - audio-deepfake-detection |
| - speech |
| - benchmark |
| - arena-ready |
| arxiv: |
| - "2410.04324" |
| --- |
| |
| # SONAR |
|
|
| Benchmark-ready packaging of the **SONAR** synthetic-audio detection evaluation set |
| ([arXiv 2410.04324](https://arxiv.org/abs/2410.04324)), for speech anti-spoofing and |
| synthetic / deepfake voice detection. |
|
|
| ## Overview |
|
|
| SONAR is a binary-classification benchmark: **bonafide** (genuine human speech) |
| vs. **spoof** (AI-synthesized speech). The spoof side aggregates clips from **eight modern |
| speech-synthesis systems**, deliberately spanning architectures and providers so that a |
| detector cannot win by memorising one generator's artifacts. The bonafide side is real |
| clips sampled from the **LibriTTS** clean-test set. Original code and data: |
| https://github.com/Jessegator/SONAR. |
|
|
| | Side | Source | n | |
| |------|--------|---| |
| | bonafide | LibriTTS clean-test | 2274 | |
| | spoof | OpenAI TTS | 600 | |
| | spoof | xTTS | 600 | |
| | spoof | FlashSpeech | 118 | |
| | spoof | VoiceBox | 104 | |
| | spoof | AudioGen | 100 | |
| | spoof | VALL-E | 95 | |
| | spoof | NaturalSpeech 3 | 32 | |
| | spoof | PromptTTS 2 | 25 | |
|
|
| > **Seed-TTS excluded (2026-06-07).** The upstream `seedtts_testset/` directory holds the |
| > SeedTTS *reference prompts* — real Common Voice audio (`common_voice_en_<prompt>-<target>.wav`), |
| > not synthesized speech (the actual SeedTTS-generated outputs are not redistributed on disk). |
| > Labeling those 600 real clips as spoof was incorrect, so they are dropped from this package. |
| > This matches the SONAR authors' own released eval set (3948 clips). |
|
|
| ## License & redistribution |
|
|
| This **packaging** is released under the **Creative Commons Attribution-NonCommercial 4.0 |
| International (CC BY-NC 4.0)** license — see `LICENSE.txt`. SONAR is an aggregate of audio |
| from multiple synthesis systems and from LibriTTS, each carrying its own upstream terms; the |
| original authors note that the constituent sources "may be subject to different distribution |
| licenses and usage restrictions." This repackaging is provided **for non-commercial research |
| use only**; the underlying sources retain their own terms, and downstream users should |
| consult the respective upstream providers' usage policies. Audio is re-encoded to 16 kHz mono |
| FLAC for a uniform schema; labels are unmodified. |
|
|
| ## Schema |
|
|
| | Column | Type | Description | |
| |--------|------|-------------| |
| | `path` | `string` | source-relative path (e.g. `OpenAI/alloy_69.wav`), unique | |
| | `audio` | `Audio(16000)` | 16 kHz mono FLAC (re-encoded from heterogeneous source wav/mp3) | |
| | `label` | `ClassLabel` | `"bonafide"` (0) / `"spoof"` (1) | |
| | `notes` | `string` | JSON: `utterance_id`, `system`, `language` | |
|
|
| `notes` example: |
| ```json |
| {"utterance_id": "SONAR_OpenAI_alloy_69", "system": "OpenAI", "language": "en"} |
| ``` |
|
|
| ## Quick Start |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("SpeechAntiSpoofingBenchmarks/SONAR", split="test") |
| print(ds[0]) |
| ``` |
|
|
| ## Stats |
|
|
| | Stat | Value | |
| |------|-------| |
| | Total trials | 3948 | |
| | Bonafide | 2274 | |
| | Spoof | 1674 | |
|
|
| ## Source provenance |
|
|
| - Paper: https://arxiv.org/abs/2410.04324 |
| - Code / data: https://github.com/Jessegator/SONAR |
| - Labels derived from the source directory layout (`real_samples/` = bonafide; the eight |
| synthesis-system directories = spoof; `seedtts_testset/` excluded — real reference prompts). |
|
|
| ## Evaluation |
|
|
| For evaluation instructions and submission format, see [`submissions/README.md`](submissions/README.md). |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{li2024sonar, |
| title = {Where are we in audio deepfake detection? A systematic analysis over |
| generative and detection models}, |
| author = {Li, Xiang and Chen, Pin-Yu and Wei, Wenqi}, |
| journal = {arXiv preprint arXiv:2410.04324}, |
| year = {2024} |
| } |
| ``` |
|
|
| ## Maintainer |
|
|
| Maintained by Kirill Borodin (SpeechAntiSpoofingBenchmarks). |
| - Email: ~~k.n.borodin@mtuci.ru~~ (deprecated — use kborodin.research@gmail.com) |
| - Telegram: [@korallll_ai](https://t.me/korallll_ai) |
|
|
