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Convtasnet Libri1Mix Enhsingle
ConvTasNet model trained on the Asteroid framework for single-channel speech enhancement tasks
Downloads 18
Release Time : 3/2/2022
Model Overview
This model adopts the ConvTasNet architecture and is trained on the enh_single task of the Libri1Mix dataset, primarily used for single-channel speech enhancement, capable of separating target speech signals from mixed audio.
Model Features
Efficient speech separation
Utilizes the ConvTasNet architecture to effectively separate target speech signals from mixed audio.
Optimized training configuration
Uses the Adam optimizer with a learning rate of 0.001, trained for 200 epochs to achieve optimal performance.
High-quality results
Achieved outstanding performance on the Libri1Mix dataset with SI-SDR 13.94 and STOI 0.92.
Model Capabilities
Single-channel speech enhancement
Audio signal separation
Speech quality improvement
Use Cases
Speech processing
Speech communication enhancement
Improves speech communication quality in noisy environments
SI-SDR improvement of 10.49dB, speech intelligibility (STOI) improvement of 0.12
Meeting recording enhancement
Separates specific speaker's voice from multi-person meeting recordings
SDR improvement of 11.06dB
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