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Deep Learning for Automatic Mixing
Deep Learning for Automatic Mixing
Audio Engineering
Music Production
Audio effects
Panning
Equalization
Compression
Reverberation
Automatic Mixing
Intelligent Music Production
Problem Formulation
Differentiable signal processing
Methods
Mix-Wave-U-Net
Differentiable Mixing Console
Loss Functions
Implementation
Inference
Datasets for automix systems
Models
Training
Evaluation
Evaluation
Listening Tests
Evaluation
Conclusion
Future Directions
Conclusions
References
repository
open issue
Index