license: apache-2.0
This repository contains the model checkpoints related to the paper: Less is More for Synthetic Speech Detection in the Wild
Dataset can be downloaded from here
🔥 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.
🚀 Stay tuned! More model checkpoints will be available soon.