speechbrain/spkrec-ecapa-voxceleb
🧠 AI Modelspeechbrain
State-of-the-art speaker embedding model using ECAPA-TDNN, trained on VoxCeleb.
The SpeechBrain ECAPA-TDNN model is a speaker recognition system that generates robust speaker embeddings. The Emphasized Channel Attention, Propagation, and Aggregation in Time Delay Neural Network (ECAPA-TDNN) architecture improves upon standard TDNN by incorporating channel attention, multi-layer feature aggregation, and residual connections. Trained on the VoxCeleb2 dataset, this model excels in speaker verification tasks, such as identifying whether two utterances are from the same speaker. It is open-source and available on Hugging Face, with easy integration via the SpeechBrain library. Key features include state-of-the-art performance on speaker verification benchmarks, efficient inference, and compatibility with PyTorch. The model outputs fixed-dimensional embeddings that can be used for downstream tasks like clustering or retrieval.
💡Highlights
- ├─ECAPA-TDNN architecture
- ├─1.5M+ HF downloads
- └─Trained on VoxCeleb2
🎯For
- ├─Speech researchers
- ├─voice biometrics developers
- └─AI audio engineers