Phase 2 Implementation

AI Music Studio

Professional melody generation and chord progression intelligence powered by RNN & Graph Neural Networks

02
Core FeaturesMelody RNN + Chord GNN
🎼

RNN Melody Completion System

Bi-directional LSTM with attention for intelligent melodic continuations

🎹
Piano Roll Editor
🧠
Model Architecture
📥

Input Embedding

MIDI pitch, duration, velocity

[B,S,128]
↔️

Bi-LSTM Layer 1

Forward + backward context

[B,S,1024]
↔️

Bi-LSTM Layer 2

Higher-level patterns

[B,S,1024]
👁️

Multi-Head Attention

8 heads, long-range

[B,S,512]
📊

Output Dense

Pitch probability

[B,S,128]
Bi-LSTMAttention30-80MB10-50ms/note
⚙️
Generation Settings
Temperature0.8
Notes to Generate16
Style
Key
📈
Statistics
0
Notes
0
Bars
--
Range
--
Avg Vel
📜
History
🎹

Graph Neural Network for Chord Progressions

GAT with multi-head attention for harmonic intelligence

🕸️
Chord Graph
Cmaj7
I
Am7
vi
Dm7
ii
G7
V
?
AI
🎻
Voice Leading
2.3
Avg Move
0
Parallel 5ths
👁️
Attention
⚙️
Settings
Genre
ComplexityMedium
Voice Lead Priority0.7
Root Key
💡
AI Suggestions
🧠
GNN Specs
📥

Chord Embed

12-dim pitch class

🕸️

GAT ×3

4 attention heads

📊

Readout

Chord probabilities

GAT10-25MB5-20ms

Model Training

Train with TensorFlow.js WebGPU

📊
Progress
Epoch
0/100
ETA
--:--
Progress0%
--
Train Loss
--
Val Loss
--
Accuracy
0.001
LR
⚙️
Config
Model
Epochs100
Batch Size32
Learning Rate0.001
💻
Hardware
Detecting...
GPU Status
📦

Export & Deploy

Export content and models

🎵
Export Content
🎹
MIDI
📄
MusicXML
{ }
JSON
🔊
WAV
🧠
Export Models
🌐
TF.js
ONNX
🍎
CoreML
📱
TFLite
🎧
Preview
⚙️
Settings
Tempo120
Format
🚀
Platforms
TensorFlow.jsWebGPUCoreMLONNXTFLite
Success