Facebook PixelMusic personalization system where AI compete in boosting/maintaining a person's mood by playing them the right music
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Music personalization system where AI compete in boosting/maintaining a person's mood by playing them the right music

Image credit: https://blog.j-labs.pl/how-does-ai-create-music

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Povilas S
Povilas S Jul 04, 2022
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Make AI compete in boosting/maintaining a person's mood by playing them the right music.
Why?
  • It is a solution to this challenge.
  • Create a super personalized music recommendation algorithm by making AI get better at playing a "game" with a given set of rules.
  • Instead of tweaking music recommendation algorithms from time to time to improve them, use an alternative way that lets maximally automatize and personalize the process.
How it works:
Similarly how AI improves in playing games like chess or goa against itself or a different AI, it can improve in games with more practical aims as long as the rules are clear.
In this case, define the aim for AI to raise the person's mood through music as much as it can, when it can't raise it, it should try to maintain it so that it at least doesn't drop further.
The mood level can be measured by the AI through different means:
  • Subjective evaluation by the person him/herself. This is the simplest approach where the user simply presses feedback buttons while the music is playing, once the feedback is below a certain threshold, the system changes the song/melody into something different and takes it from there. If the feedback is rather good, it tries to include more similar songs/melodies.
  • Physiological parameters. The data about the person's brain activity (especially that of the limbic system), heartbeat, breathing, electrodermal activity, skin temperature, etc. is sent to the AI while the music is playing. Those are continuous and more objective measures if you know how to convert the data into mood scores. Currently, wireless sensor systems are well developed and don't require bulky wires or for the user to sit in one place, devices similar to the Muse headband and Empatica wristband can be used to build the system.
  • Combination of the two. I think the smartest way to go about this would be to first correlate an individual's physiological parameters with their subjective mood evaluations and then create an "atlas" for AI to convert continuously monitored physiological parameters into mood scores. This could be done in a preparatory phase and then the system would keep refining the connections between physiological data and subjective mood evaluation as the user gives subjective feedback while listening to the music.
An AI could compete either against itself or a different AI - a tweaked algorithm. It would take turns in playing songs just like it takes turns in making moves in a board game, after each turn, the situation would be adjusted according to the person's mood level.
Instead of selecting pre-recorded songs, AI could also mix different melodies together and even create music. Turns as moves in the game could be defined as playing music for limited time intervals, like 1 minute or till the feedback from the user drops under a certain threshold.
First feed the AI all the person's listening history, playlists, etc. Then make it learn further in the process from the user's feedback while listening to its selected/made music. If the result is not good enough after a certain time, tweak the algorithm a bit and make it play against the old version. Repeat until the results are satisfactory.
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General comments

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Florin Buda
Florin Buda5 months ago
What if I'm at work and I run your app that allways calm me but suddenly i receive a horrible email and my zen is going nuts? The song i'm listening would be downvoted until oblivion?
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J. Nikola
J. Nikola5 months ago
The idea is very cool in theory. I would love to hear some uplifting music when I feel down. What concerns me is that in practice, the AI would end up playing with you for hours, spending your time without the expected positive mood change. In addition to the length of the songs (3-4 mins on average), every song provokes different memories and thus, different mood changes. Although the algorithm would track our mood changes and feedback, I am not sure that's enough to pick the right song that would lift us up. I am almost never successful in doing that to myself. Some songs I enjoy only at the beginning, but they soon become boring. Some last too long. Some I love but today is just not the day. If I feel down this evening, I wouldn't be uplifted by the song that lifted me this morning. In other words, mood changes and songs are very connected but very complex. Maybe I just need stronger proof that the AI is capable of doing it all and bring us joy :)
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Povilas S
Povilas S5 months ago
J. Nikola Yes, those are all perfectly valid points. And they are exactly the reason why I think that only strong AI, if anything, could crack the lock to your mood through music. It's quite easy to view the fitting of the right music for the moment to raise a person's mood as an equation to solve, a function. Many variables go into the making of it that need to be figured out, it's complex, but not impossible:)
And to achieve this, it should be done for each person separately, not end up as a generalized algorithm for all users. This should be first tested in trials with separate individuals and if proven to work, could be sold as a super-personalized artificial DJ system.
I think AI could learn pretty much solely from your listening history and data about your online behavior. And then long periods of testing and training with the person would be needed, yes, but I think it's absolutely worth it, given the desired end result is successful.
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Povilas S
Povilas S5 months ago
J. Nikola Also, the system doesn't have to wait for the whole song to be over, as soon as the user's feedback either manual (they press downvote, a 6 out of 10, etc.) or automatic (extracted from physiological data) drops below a certain threshold, AI would change the music into a different one and take it from there.
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