TAREA 06: Preset Generation - Intelligent Preset Creation¶
Status: 🔴 PLANNING
🎯 Purpose¶
AI-powered preset generation, recommendation, and style transfer for audio effects and synthesizers.
🏗️ Key Components¶
- Audio-to-Preset Mapping: Inverse synthesis from reference audio
- Preset Recommendation: Collaborative filtering, content-based filtering
- Style Transfer: Apply characteristics of reference to effect chain
- Preset Interpolation: Smooth morphing between presets
📋 Architecture¶
class PresetGenerator {
public:
// Generate preset from target audio
ParameterSet generateFromAudio(
const IAudioProcessor& processor,
const std::vector<float>& target_audio,
const std::vector<float>& input_audio
);
// Recommend presets based on audio content
std::vector<Preset> recommendPresets(
const std::vector<float>& audio,
int num_recommendations = 5
);
// Interpolate between presets
Preset interpolate(const Preset& a, const Preset& b, float t);
// Learn user preferences
void updateUserModel(const Preset& preset, float rating);
};
🎯 Use Cases¶
- "Make it sound like X" feature
- Genre-aware preset suggestions
- Automatic preset generation from reference
- User profile-based recommendations
- Preset morphing and blending
📚 Techniques¶
- Inverse Synthesis: Differentiable DSP + gradient descent
- Collaborative Filtering: User-preset interaction matrix
- Content-Based Filtering: Audio feature similarity
- Embedding Space: Latent representation of presets
🔧 Example¶
PresetGenerator generator;
generator.initialize("models/preset_recommender.onnx");
// Load reference audio
auto reference = loadAudio("reference_track.wav");
// Generate matching preset for compressor
CompressorDSP compressor;
auto preset = generator.generateFromAudio(
compressor,
reference,
input_audio
);
// Apply generated preset
compressor.setParameters(preset);
Priority: 🟡 Medium - Enhances user experience significantly