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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
Fx-Normalization
Differentable Mixing Style transfer
Loss Functions
Implementation
Inference
Datasets for automix systems
Models
Training
Evaluation
Evaluation
Evaluation
Listening Tests
Evaluation
Conclusion
Future Directions
Conclusions
References
Repository
Open issue
Index
