201–210 of 444 posts
I've never commented on HN before, but I feel compelled. Congrats, you get my first. I've been using your site for 10 minutes and already added song after song to my library. I'm sure you'll improve the matching algorithm over time. This is a great first step; I'm being exposed to songs I've never come across before. Good job!
You are into something here I am telling you, while spotify does provide recommendations of what you would like to hear, it does not provide similar sounding songs, as a musician I love it.
Will definitely work to improve the current model!
It's actually great. I got a ton of good recommendations. The key is to actually use it to search songs of similar beat or tone.
But a lot of this should go away with a better, improved model!
I have a human-powered recommendation service that uses my own tags that I've added to my mp3 library over 25 years. I add instruments (not all, just the ones that stands out, like synth, flute, distortion, violin, piano), vocals (male/female, falsetto, spoken, rap), moods (happy, sad, angry, mellow, dramatic, chillout) and genre (I don't go too deep here, because I hate getting recommendations stuck within some obscure sub-genre). And that's it. I get it to play a random highly rated track with a keyword or two, and then use the tags from the first 10 songs to generate the next. But since, for me, music is a somewhat interactive experience, every 10 songs or so, I'll think of something that I want on the list (maybe reminded of it by another one that just played).
Other things I think might be useful for recommendation is Last.FM histories. Think about it, the are hundreds of thousands of active listeners "scrobbling" their listening history. You could easily parse that and group songs together that have been played within 5 songs of each other as long as they're not by the same artist and the time between the songs is around zero (ie: listened to in order, no pauses). Similarity is higher for songs that were next to each other and score drops.
I've found probably the most egregious example of what knaik94's comment is talking about: https://maroofy.com/songs/214977681 ("Being Alive" from Company) All the AI model seems to understand is the opening 5 seconds piano. Listen to the actual song it just opens like that because it's from a play. I think this will struggle with any song that has build up, it's very promising, though you need a sample of entire son…
I actually think this is largely in part due to how the current model + training process is designed.
I have some ideas for improving things on this front, will give it a try and push an update soon! :)
I love the idea, but the results were far off the mark. Perhaps they should be weighted according to some vectors, including language. I chose 'Let it be me' by the Everly Brothers. 8 or so of the top 10 were foreign songs, and sounded much older even.
Tried Erreur 404 by L'Impératrice[1], and I noticed the beat of the other recommended songs were eerily similar!! I'd argue your project is actually too good. Where Spotify's Discover Weekly tried to connect you to music other people listen to {B, C, D, ...} because you've listened to a particular song {A} {B...->A}, your model quite literally tried to find other music {A₂} that sounds like what you're looking for {A…
I find it disheartening that the comments are loaded with people saying how bad it is. The interface is awesome, the ability to have search results pop up and offer suggestions is impressive. I thought the results for a Lana Del Ray song and a song by Carlos Santana were both interesting and suggested new things. We should do a better job of supporting creators here.
Great initiative, but if it's sampling only the few seconds previews from the songs, then I doubt it will be useful. Also, a language filter is essential for both training the model and listing the results. I searched for a few Hindi language songs that I know of, and it listed only English, Chinese and Spanish songs as related ones - which is good to explore other music, but at times I'd just want to be in my native…
Thank you. This is really great. Of course not everything is a hit but it did find some beautiful tunes for me. One little problem: if you press play and wander off after it stopped playing it can be rather hard to find what you played.
Also, as I improve the model & add user accounts, recommendations should hopefully get much better and more personalized!