See the following websites:
Using conda, do the following:
conda create --name py2 python=2.7
pip install --upgrade https://github.com/Theano/Theano/archive/master.zip
pip install --upgrade https://github.com/Lasagne/Lasagne/archive/master.zip
git clone https://github.com/IraKorshunova/folk-rnn.git
cd folk-rnnThen to generate using one of the pretrained models:
python sample_rnn.py --terminal metadata/folkrnn_v2.pklTo train a new model:
python train_rnn.py config5 data/v2_dataThis code was used for the following published works:
Sturm and Ben-Tal, "Folk the algorithms: traditional music in AI music research", The Sound of AI (Medium)
Sturm and Ben-Tal, "Let’s Have Another Gan Ainm: An experimental album of Irish traditional music and computer-generated tunes"
Sturm, Ben-Tal, Monaghan, Collins, Herremans, Chew, Hadjeres, Deruty and Pachet, “Machine learning research that matters for music creation: A case study,” J. New Music Research 48(1):36-55, 2018.
Sturm "How Stuff Works: LSTM Model of Folk Music Transcriptions", invited presentation Joint Workshop on Machine Learning for Music, 2018.
Sturm, “What do these 5,599,881 parameters mean? An analysis of a specific LSTM music transcription model, starting with the 70,281 parameters of its softmax layer,” in Proc. Music Metacreation workshop of ICCC, 2018.
Sturm and Ben-Tal, "Taking the Models back to Music Practice: Evaluating Generative Transcription Models built using Deep Learning,” J. Creative Music Systems, Vol. 2, No. 1, Sep. 2017.
Sturm, Santos, Ben-Tal and Korshunova, "Music transcription modelling and composition using deep learning", in Proc. 1st Conf. Computer Simulation of Musical Creativity, Huddersfield, UK, July 2016.
Sturm, Santos and Korshunova, "Folk Music Style Modelling by Recurrent Neural Networks with Long Short Term Memory Units", Late-breaking demo at the 2015 Int. Symposium on Music Information Retrieval
The folk-rnn v1, v2 and v3 Session Books https://highnoongmt.wordpress.com/2018/01/05/volumes-1-20-of-folk-rnn-v1-transcriptions/
47,000+ tunes at The Endless folk-rnn Traditional Music Session http://www.eecs.qmul.ac.uk/~sturm/research/RNNIrishTrad/index.html
"Cloudberry Lane" by Zoë Gorman + folk-rnn (2019) https://youtu.be/6-XDhZ_AVGQ
Laura Agnusdei and guest perform some output of folkrnn at the 2019 ReWire festival https://www.thoughtsource.org/vimeo_tab/app/tab/view_video?fbPageId=109823292380435&page=1&videoId=345886314
"Bastard Tunes" by Oded Ben-Tal + folk-rnn (v2) (2017) https://www.youtube.com/playlist?list=PLdTpPwVfxuXpQ03F398HH463SAE0vR2X8
"Safe Houses" by Úna Monaghan + folk-rnn (v2) (for concertina and tape, 2017) https://youtu.be/x6LS9MbQj7Y
"Interpretations of Computer-Generated Traditional Music" by John Hughes + folk-rnn (v2) (for double bass, 2017) https://youtu.be/GmwYtNgHW4g
"Dialogues with folk-rnn" by Luca Tuchet + folk-rnn (v2) (for smart mandolin, 2017) https://youtu.be/pkf3VqPieoo; at NIME 2018 https://youtu.be/VmJdLqejb-E
"The Fortootuise Pollo" by Bob L. Sturm + folk-rnn (v1) (2017) https://soundcloud.com/sturmen-1/the-fortootuise-pollo-1
"March to the Mainframe" by Bob L. Sturm + folk-rnn (v2) (2017) Performed by Ensemble x.y: https://youtu.be/TLzBcMvl15M?list=PLdTpPwVfxuXrdOyjtwfokrpzfpIlnJc5o Performed by Ensemble Volans: https://soundcloud.com/sturmen-1/march-to-the-mainframe-by-bob-l-sturm-folk-rnn-v2 Score is here: https://highnoongmt.files.wordpress.com/2017/12/twoshortpieceswithaninterlude.pdf
"Interlude" by Bob L. Sturm + folk-rnn (v2) (2017) Performed by Ensemble x.y: https://youtu.be/NZ08dDdYh3U?list=PLdTpPwVfxuXrdOyjtwfokrpzfpIlnJc5o Performed by Ensemble Volans: https://soundcloud.com/sturmen-1/interlude-by-bob-l-sturm-folk-rnn-v2 (synthesized version: https://soundcloud.com/sturmen-1/interlude-synthesised) Score is here: https://highnoongmt.files.wordpress.com/2017/12/twoshortpieceswithaninterlude.pdf
"The Humours of Time Pigeon" by Bob L. Sturm + folk-rnn (v1) (2017) Performed by Ensemble x.y: https://youtu.be/1xBisQK8-3E?list=PLdTpPwVfxuXrdOyjtwfokrpzfpIlnJc5o Performed by Ensemble Volans: https://soundcloud.com/sturmen-1/the-humours-of-time-pigeon-by-bob-l-sturm-folk-rnn-v1 (synthesized version: https://soundcloud.com/sturmen-1/the-humours-time-pigeon-synthesised) Score is here: https://highnoongmt.files.wordpress.com/2017/12/twoshortpieceswithaninterlude.pdf
"Chicken Bits and Bits and Bobs" by Bob L. Sturm + folk-rnn (v1) (2017, 2019) https://soundcloud.com/sturmen-1/chicken-bits-and-bits-and-bobs Score is here: https://highnoongmt.files.wordpress.com/2017/04/chicken_score.pdf
"The Ranston Cassock" by Bob L. Sturm + folk-rnn (v1) (2016) https://youtu.be/JZ-47IavYAU (Version for viola and tape: https://highnoongmt.wordpress.com/2017/06/18/the-ranston-cassock-take-2/)
Tunes by folk-rnn harmonised by DeepBach (2017)
Tunes from folk-rnn v1 session volumes
Tunes from the folk-rnn v2 session volumes
Tunes from the folk-rnn v3 session volumes
"Why are you and your 6 million parameters so hard to understand?" by folk-rnn (v2) and Bob L. Sturm (2018) https://highnoongmt.wordpress.com/2018/01/21/making-sense-of-the-folk-rnn-v2-model-part-8/
"Two Burner Brew No. 1" by folk-rnn (v2) and Bob L. Sturm and Carla Sturm (2018) https://soundcloud.com/sturmen-1/two-burner-brew-no-1
"A Windy Canal" by folk-rnn (v2) and Bob L. Sturm (2018) https://highnoongmt.wordpress.com/2018/01/11/making-sense-of-the-folk-rnn-v2-model-part-6/
"Swing Swang Swung" by folk-rnn (v2) and Bob L. Sturm (2018) https://youtu.be/Y_DBRg6SK7E (analysis here: https://highnoongmt.wordpress.com/2018/01/03/making-sense-of-the-folk-rnn-v2-model-part-5/ )
"Experimental lobotomy of a deep network with subsequent stimulation (2)" by folk-rnn (v2 with lobotomy) and Bob L. Sturm, Carla Sturm (2018) https://highnoongmt.wordpress.com/2018/01/13/making-sense-of-the-folk-rnn-v2-model-part-7/
"The Millennial Whoop Reel" by Bob L. Sturm + folk-rnn (v2) (2016) https://highnoongmt.wordpress.com/2016/08/29/millennial-whoop-with-derp-learning-a-reel/
"The Millennial Whoop Jig" by Bob L. Sturm + folk-rnn (v2) (2016) https://highnoongmt.wordpress.com/2016/08/28/millennial-whoop-with-derp-learning/
"Eight Short Outputs ..." by folk-rnn (v1) + Bob L. Sturm (2015) https://highnoongmt.wordpress.com/2015/12/20/eight-short-outputs-now-on-youtube/
"Carol of the Cells" by Bob L. Sturm + folk-rnn (v2) (2017) https://highnoongmt.wordpress.com/2017/12/16/carol-of-the-cells-from-the-ai-to-the-orchestra/
"It came out from a pretrained net" by Bob L. Sturm + folk-rnn (v2) (2016) https://highnoongmt.wordpress.com/2016/12/24/taking-a-christmas-carol-toward-the-dodecaphonic-by-derp-learning/
“We three layers o’ hidd’n units are” by Bob L. Sturm + folk-rnn (v2) (2015) https://highnoongmt.wordpress.com/2015/12/16/tis-the-season-for-some-deep-carols/
"The March of Deep Learning" by Bob L. Sturm + folk-rnn (v1) (2015) https://highnoongmt.wordpress.com/2015/08/15/deep-learning-for-assisting-the-process-of-music-composition-part-4/