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| title: WhAM | |
| emoji: 🐋 | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: docker | |
| pinned: false | |
| hardware: a10g-small | |
| # WhAM: a Whale Acoustics Model | |
| WhAM is a transformer-based audio-to-audio model designed to synthesize and analyze sperm whale codas. It uses masked acoustic token modeling to capture the unique temporal and spectral features of whale communication. | |
| For full technical details, installation instructions, and training scripts, please visit the official repository at [https://github.com/Project-CETI/wham]. | |
| ## Citation | |
| If you use this code, model, or data in your research, please cite our [NeurIPS 2025](https://openreview.net/pdf?id=IL1wvzOgqD) publication: | |
| ```bibtex | |
| @inproceedings{wham2025, | |
| title={Towards A Translative Model of Sperm Whale Vocalization}, | |
| author={Orr Paradise, Pranav Muralikrishnan, Liangyuan Chen, Hugo Flores Garcia, Bryan Pardo, Roee Diamant, David F. Gruber, Shane Gero, Shafi Goldwasser}, | |
| booktitle={Advances in Neural Information Processing Systems 39: Annual Conference | |
| on Neural Information Processing Systems 2025, NeurIPS 2025, San Diego, CA, USA}, | |
| year={2025} | |
| } | |