I recently read a review about current neural network approaches to music generation. It's fascinating how models learn to recognize harmony and rhythm structures and then create original compositions without human intervention. Which architectures are considered the most promising in this field? How does the size of the training dataset affect the quality of the resulting compositions? It would be great to gather links to open research and conduct some small experiments. Share your thoughts and experiences! 🎹
How do neural networks evolve in creative music?
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I'm particularly interested in how long-term harmonic dependencies are handled in transformer-like architectures (e.g., MusicLM). Could you clarify how critical the size of the training dataset is for achieving a stable musical theme?