Project Title: Interactive Music Generation with Python.
Description:
This project empowers users to create unique musical pieces by interactively specifying chords and leveraging the power of Python for automatic music generation. It combines user creativity with machine learning to produce personalized compositions.
Key Features:
User-Driven Chord Selection: Users can create chord progressions by selecting chords from a visual interface or entering them directly using music theory notation. Machine Learning Model: An LSTM (Long Short-Term Memory) network, trained on a diverse MIDI dataset, generates melodies that complement the user-defined chords. MIDI Output: The generated music is exported as a MIDI file, allowing users to play it back on various digital instruments or music software. Customization Options (Optional): Users may be able to adjust parameters like tempo, rhythm, and instrumentation to further personalize the output. Explore advanced features like genre selection or style transfer mechanisms based on additional user input.