So what's the activation function on the last layer? Linear?
With the intriguing exception of the Global Temporal Pooling layer, this matches up with a lot of my ideas for music analysis. Nice work!
Recommending music on Spotify with deep learning
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Re: Recommending music on Spotify with deep learning
#12Great post! It was fun to see 4 tracks in the (first convolutional layer) filter 242 set that I recognized from my own 'ambient' Spotify playlists, and pretty impressive at the topmost layer as well. Loved that approach of looking at a few tracks that represented maximally or average activated filters.
Curious if you think the low-level features learned from the vector_exp latent factors are different from, say, unsupervised learning with sparse autoencoders? For example, are there phonemes associated with Chinese pop or Spanish rap that are learned at a low level, that the network might not learn with "unlabeled" data?
Re: Recommending music on Spotify with deep learning
#13Nice post - i am not extremely familiar with mel-spectrograms but I was wondering if you have considered using an advanced wavelet transforms as features?
Re: Recommending music on Spotify with deep learning
#14Is it possible to get my own listing history natively from Spotify? I'm not interesting in scrobbling to another service, etc. Seems like this should be a well documented and used service from the Spotify API, but as far as I know, it does not exist.
I once heard that they don't store that info, though I would love to be proven wrong.
They definitely store it, as you can find it on the Play Queue page under the "History" tab.
Re: Recommending music on Spotify with deep learning
#15Great post! It was fun to see 4 tracks in the (first convolutional layer) filter 242 set that I recognized from my own 'ambient' Spotify playlists, and pretty impressive at the topmost layer as well. Loved that approach of looking at a few tracks that represented maximally or average activated filters. Curious if you think the low-level features learned from the vector_exp latent factors are different from, say, unsu…
I haven't tried it, so I can't say for sure, but my intuition is that learning to predict the latent factors is a much less 'complex' task than learning good features to reconstruct the input (i.e. the spectrograms), in terms of the required capacity of the model.
With a purely unsupervised approach, you are basically wasting capacity on modeling aspects of the data that are relevant for reconstructing the input, but not for solving the task at hand. For example, the model doesn't have to care about precise pitches and timing, because those are not relevant for recommendation (and latent factor prediction) anyway. That means no model capacity is wasted on these things. With a fairly complex task such as this one, I think that probably makes a big difference.
Re: Recommending music on Spotify with deep learning
#16Nice post - i am not extremely familiar with mel-spectrograms but I was wondering if you have considered using an advanced wavelet transforms as features?
I haven't really optimized that part of the pipeline, for now I'm just using what I always use because getting the data and massaging it into the right format is quite time consuming.
There is a lot of knowledge about good time-frequency representations for music analysis among the people who were formerly at The Echno Nest (which was acquired by Spotify a few months ago), so it would definitely be a good idea to apply their knowledge to this and come up with a better input representation. I only have a few weeks left though, so it doesn't have a high priority at the moment :)
Re: Recommending music on Spotify with deep learning
#17So what's the activation function on the last layer? Linear? With the intriguing exception of the Global Temporal Pooling layer, this matches up with a lot of my ideas for music analysis. Nice work!
Yep, it's linear. This is essentially a regression task and the distribution of the factors across the dataset is pretty close to Gaussian in most cases, so it made sense not to have any nonlinearities there.
As a sidenote, if it weren't for the L2-pooling in the global temporal pooling layer, the network would be completely piecewise linear from input to output :)
Re: Recommending music on Spotify with deep learning
#18Earlier quoted context omitted.
I once heard that they don't store that info, though I would love to be proven wrong.
They definitely store it, as you can find it on the Play Queue page under the "History" tab.
I think that this data is only local to each computer. I use spotify on two computers and the phone: The history tab does not sync between these devices.
Re: Recommending music on Spotify with deep learning
#19This would be awesome. The one problem I've had with Spotify's radio service is only being able to pick up on genres and such. Many times I might like only 1 or 2 bands from a more obscure genre, but spotify radio does not understand this no matter how many songs I downvote. In fact, my "starred" playlist radio is currently stuck on some kind of 80s metal thing. I have no idea how it got that way, but it refuses to p…
I've had a similar experience. At one point the radio was 90% Childish Gambino despite only having one of his songs in my playlist
Re: Recommending music on Spotify with deep learning
#20Great stuff! However, I thought that the Echo Nest tools that they bought were already doing such stuff. If not, what are they currently using for content-based recommendation?