214 points by deepmusicguy 1 year ago flag hide 11 comments
deeplearningmusic 1 year ago next
Excited to share my latest project - Personalized Neural Network Music Composition! This app uses AI to generate personalized music pieces based on the user's preferences and listening history. Would love to hear your thoughts and feedback.
hacker1 1 year ago prev next
@deeplearningmusic This is incredible! I've tried it out and the music it generated for me is awesome! So curious as to how the AI is trained. Any details you'd be willing to share on your methodology?
deeplearningmusic 1 year ago next
@hacker1 Thanks for your kind words! I used a combination of recurrent neural networks and long short-term memory networks (RNN-LSTM) to analyze and predict musical sequences. I also employed a genre classification algorithm to suggest styles of music based on users' listening history. Feel free to reach out if you'd like more comprehensive details!
hacker2 1 year ago prev next
@deeplearningmusic I just tried it and was impressed at how well the AI generated music according to my tastes. I am curious about the data augmentation techniques used on your training dataset to prevent overfitting?
deeplearningmusic 1 year ago next
@hacker2 Thank you! I applied data augmentation techniques such as random pitch and tempo adjustments and time stretch in order to encourage the neural network to be more robust and generalizable. I also employed ensemble methods of multiple neural networks, which improved the generated music.
hacker3 1 year ago prev next
Really neat something like this! I'd be curious about how you handle real-time composition and whether it can accommodate user input during the creation process?
deeplearningmusic 1 year ago next
@hacker3 Great question! I employed techniques like dynamic evaluation and real-time sequence prediction for the composition to stay responsive to user input while actively appending musical constraints to the input of the neural network. This results in a more engaging, interactive experience for users.
hacker4 1 year ago prev next
Just checked this out and it's impressive! Feeding MIDI data directly into an LSTM leads to convincing results, but I'd like to understand the value added by other techniques discussed here. Did you use any transfer learning or fine-tuning strategies?
deeplearningmusic 1 year ago next
@hacker4 Absolutely! In addition to raw MIDI data, I utilized pre-trained genre classifiers and transfer learned its layers and extracted features using a smaller dataset. This helped with fine-tuning the output for specific genres and generated music more in line with user preferences.
hacker5 1 year ago prev next
I tried this with some friends and we were all astounded by the personalized music. How do you manage tempo and meter transitions to ensure a smooth flow between musical sections?
deeplearningmusic 1 year ago next
@hacker5 Thanks for the feedback! I implemented a multi-layered loss function that includes tempo and meter transition constraints in addition to the standard music generation losses. This ensures a smooth flow and a realistic, seamless composition across the generated sections.