danieldjohnson/biaxial-rnn-music-composition

Health v2 · maintenance only

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Adoption not part of the score

1926 stars · 371 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python implementation of a biaxial recurrent neural network (LSTM-based) trained to generate classical music from MIDI data. It includes training and composition-generation code built on Theano.

Use cases

• generate classical music with a neural network
• train an LSTM on MIDI files to compose music
• produce AI-generated musical compositions
• experiment with recurrent networks for music composition
• sample new pieces from a trained music model

When to choose

• you want to generate classical-style music from a corpus of MIDI files
• you want a reference implementation of biaxial RNN music composition
• you are studying or extending LSTM-based music generation models

When to avoid

• you need a maintained, modern deep-learning stack (it depends on the deprecated Theano library)
• you want real-time or production music generation
• you need multi-instrument or non-4/4-time MIDI support out of the box

Facets

library · maturity maintenance

machine-learning deep-learning llm-training machine-learning deep-learning media python music-generation lstm rnn midi theano algorithmic-composition audio linux gpu

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markdown · JSON · MCP: product_card(name="danieldjohnson/biaxial-rnn-music-composition")