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| license: cc-by-nc-4.0 |
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| # MultiAPI Spoof: Multi-Source Audio Anti-Spoofing Dataset |
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| ## Introduction |
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| MultiAPI-Spoof is a multi-source audio anti-spoofing dataset that contains approximately 230 hours of spoofed audio. It includes synthetic audio generated by commercial TTS services, open-source models, and Chinese TTS websites. An equal amount of bonafide speech from CommonVoice is included for a 1:1 balance between genuine and spoofed samples. This dataset is designed to support research and model training for audio anti-spoofing. |
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| - 📥 [Download dataset](https://ofspectrum.com/api/download) or [Download on huggingface](https://huggingface.co/datasets/XuepingZhang/MultiAPI_Spoof) |
| - 📄 [Paper on arXiv](https://arxiv.org/abs/2512.07352) |
| - 🖥️ [Code on github](https://github.com/XuepingZhang/MultiAPI-Spoof) |
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| ## Spoofed Audio Data Sources |
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| Our new dataset, **MultiAPI Spoof**, contains speech samples generated from a variety of API sources, including: |
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| 1. **Commercial TTS APIs** – speech generated by commercial services. |
| 2. **Open-Source Model Generation** – speech generated by open-source models. |
| 3. **TTS Websites** – speech on TTS web platforms. |
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| The dataset is organized into 30 API, labeled **A0–A29**, with each group corresponding to a unique speech generation API source. The duration of speech in each API ranges from **0.2 to 12 hours**. |
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| ## Dataset Split |
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| | API NO. | train | dev | eval | |
| | :------ | :---- | :--- | ---- | |
| | A0-A20 | 70% | 10% | 20% | |
| | A21-A23 | / | 100% | / | |
| | A24-A29 | / | / | 100% | |
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| *** |
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| ## Metadata |
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| The dataset includes three metadata files: MultiAPI`_train.txt`, MultiAPI`_dev.txt`, and MultiAPI`_eval.txt`. |
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| Each line has four fields: |
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| audio_path api class_label |
| XXX.mp3 A0 spoofed |
| XXX.mp3 - bonafide |
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| ## 📖 Citation |
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| If you use this code or dataset, please cite: |
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| ``` |
| @misc{zhang2025multiapispoofmultiapidataset, |
| title={MultiAPI Spoof: A Multi-API Dataset and Local-Attention Network for Speech Anti-spoofing Detection}, |
| author={Xueping Zhang and Zhenshan Zhang and Yechen Wang and Linxi Li and Liwei Jin and Ming Li}, |
| year={2025}, |
| eprint={2512.07352}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.SD}, |
| url={https://arxiv.org/abs/2512.07352}, |
| } |
| ``` |
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| ## 🔏 License |
| The dataset is released under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/deed.en) license. |
| Users must comply with the license terms. The authors do **not** claim ownership of the original audio content. |
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| ## Contact |
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| For questions or suggestions, please contact: [zxp9921@gmail.com](zxp9921@gmail.com) |
