| | --- |
| | license: apache-2.0 |
| | language: |
| | - en |
| | - zh |
| | - ja |
| | tags: |
| | - audio |
| | - synthetic-speech-detection |
| | - deepfake |
| | - deepfake-audio |
| | - security |
| | - voice-spoofing |
| | - anti-spoofing |
| | configs: |
| | - config_name: tts |
| | data_files: |
| | - split: test |
| | path: TTS/*.tar.gz |
| | - config_name: real |
| | data_files: |
| | - split: test |
| | path: real_data_flac/*.tar.gz |
| | - config_name: vocoders |
| | data_files: |
| | - split: test |
| | path: Vocoders/**/*.tar.gz |
| | --- |
| | This repository introduces: 🌀 *ShiftySpeech*: A Large-Scale Synthetic Speech Dataset with Distribution Shifts |
| |
|
| | ## 🔥 Key Features |
| | - 3000+ hours of synthetic speech |
| | - **Diverse Distribution Shifts**: The dataset spans **7 key distribution shifts**, including: |
| | - 📖 **Reading Style** |
| | - 🎙️ **Podcast** |
| | - 🎥 **YouTube** |
| | - 🗣️ **Languages (Three different languages)** |
| | - 🌎 **Demographics (including variations in age, accent, and gender)** |
| | - **Multiple Speech Generation Systems**: Includes data synthesized from various **TTS models** and **vocoders**. |
| | |
| | ## 💡 Why We Built This Dataset |
| | > Driven by advances in self-supervised learning for speech, state-of-the-art synthetic speech detectors have achieved low error rates on popular benchmarks such as ASVspoof. However, prior benchmarks do not address the wide range of real-world variability in speech. Are reported error rates realistic in real-world conditions? To assess detector failure modes and robustness under controlled distribution shifts, we introduce **ShiftySpeech**, a benchmark with more than 3000 hours of synthetic speech from 7 domains, 6 TTS systems, 12 vocoders, and 3 languages. |
| |
|
| | ## ⚙️ Usage |
| |
|
| | Ensure that you have soundfile or librosa installed for proper audio decoding: |
| |
|
| | ```bash |
| | pip install soundfile librosa |
| | ``` |
| | ##### 📌 Example: Loading the AISHELL Dataset Vocoded with APNet2 |
| |
|
| | ```bash |
| | from datasets import load_dataset |
| | |
| | dataset = load_dataset("ash56/ShiftySpeech", data_files={"data": f"Vocoders/apnet2/apnet2_aishell_flac.tar.gz"})["data"] |
| | ``` |
| | **⚠️ Note:** It is recommended to load data from a specific folder to avoid unnecessary memory usage. |
| |
|
| | The source datasets covered by different TTS and Vocoder systems are listed in [tts.yaml](https://huggingface.co/datasets/ash56/ShiftySpeech/blob/main/tts.yaml) and [vocoders.yaml](https://huggingface.co/datasets/ash56/ShiftySpeech/blob/main/vocoders.yaml) |
| |
|
| | ## 📄 More Information |
| |
|
| | For detailed information on dataset sources and analysis, see our paper: *[ShiftySpeech: A Large-Scale Synthetic Speech Dataset with Distribution Shifts](https://arxiv.org/pdf/2502.05674)* |
| |
|
| | You can also find the full implementation on [GitHub](https://github.com/Ashigarg123/ShiftySpeech/tree/main) |
| |
|
| | ### **Citation** |
| |
|
| | If you find this dataset useful, please cite our work: |
| | ```bibtex |
| | @article{garg2025shiftyspeech, |
| | title={ShiftySpeech: A Large-Scale Synthetic Speech Dataset with Distribution Shifts}, |
| | author={Garg, Ashi and Cai, Zexin and Zhang, Lin and Xinyuan, Henry Li and Garc{\'\i}a-Perera, Leibny Paola and Duh, Kevin and Khudanpur, Sanjeev and Wiesner, Matthew and Andrews, Nicholas}, |
| | journal={arXiv preprint arXiv:2502.05674}, |
| | year={2025} |
| | } |
| | ``` |
| |
|
| | ### ✉️ **Contact** |
| |
|
| | If you have any questions or comments about the resource, please feel free to reach out to us at: [agarg22@jhu.edu](mailto:agarg22@jhu.edu) or [noa@jhu.edu](mailto:noa@jhu.edu) |
