Singing about tensorflow-wavenet HOT 9 CLOSED

It'll probably be easier to find annotations in MIDI, there are not that
many people transcribing melodies with Lilypond. The issue is usually to
align the annotations to the audio; in speech recognition it's common to
learn the alignment as well as the phoneme discrimination. Datasets from
the MIREX challenges are probably a good starting point for the search.

El dg., 18 set. 2016 a les 6:45, bhack ([email protected]) va
escriure:

It could be really interesting to train with singing solo tracks and
Lilypond
http://lilypond.org/doc/v2.19/Documentation/notation/common-notation-for-vocal-music.
But probably could be too hard to collect a datest handing copyrights
issues.

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Take a look at MedleyDB, they have F0 annotations for individual stems for a couple hundred songs if I remember correctly:
http://medleydb.weebly.com/

Edit:
SonicVisualizer is also a great tool to get annotation data (f0 ground truth, chord estimates, etc) from audio.

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There is a Lilypond archive called Mutopia project but it is for classical music.
Probably for singing could trained using GT from
Mirex Voice Separation

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Another possible option is to contact audio-lyrics alignment people who are working in a capella singing voice.

I'm not familiar if there are any easy-to-reach datasets but @georgid might help you guys pinpointing some. In fact he has a dataset too (https://github.com/MTG/turkish-makam-acapella-sections-dataset), but I'm not sure if the size is adequate and the music style is too specific for your preferences...

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Adding to @lemonzi's suggestion, I recommend checking out @craffel's recently released Lakh MIDI Dataset. It provides a large set of MIDI files that have been aligned to songs in the Million Song Dataset.

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/cc @osageev

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If you need only f0-annotations, then I can add to the already suggested ones:
RWC (annotations in MIDI) and iKala datasets.
Maybe the only dataset big enough for DNNs, which is NOT annotated, but might be worth trying doing it, is: DAMP

If you need lyrics annotations as well have a look at this list:
https://docs.google.com/document/d/1PAIshZ6ZpAl7ad2GiiT6Y3wFyrfFkSj4f0wok6yN4j0/edit?usp=sharing

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Hi,
I just tried training on bird's "song", which is commonly used for the study of language in neuroscience, and it seems learning really nicely. :)
I wrote simple background and results on my repo (https://github.com/shiba24/birdsong-generation-project). Although this is not human song or music, any feedback and/or comments will be welcomed if you kindly though it's interesting! Thank you.

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https://arxiv.org/abs/1704.03809 and http://www.dtic.upf.edu/~mblaauw/IS2017_NPSS/

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