folk-rnn (v2) 28001

Taken from the folk-rnn (v2) Session Book Volume 10 of 10
https://highnoongmt.wordpress.com/2018/01/05/volumes-1-20-of-folk-rnn-v1-transcriptions/

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Interpretations of Computer-Generated Traditional Music, by John Hughes

Added by folkrnn admin,
June 28, 2018.

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M:6/8
K:Gmaj
b<d’d g2d|efg a2b|c’<c’a e2g|abc’ bag|
b>dg d2g|e<fg a2b|c’>ba g>fe|1g>fe d2c’:|
|2g>ed d2c’|b/2c’/2d’b g2b|gfe d2d|e>fg aba|
g>fe d2c’|b>c’d’ b2g|gfe a2d|g>c’b adf|
g3 g2a|b/2c’/2d’b g2b|g>c’b e2f|efg fed|
e>gf edc|Bcd def|g>ab a2b|c’>ba gfe|
d2e d2|

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Interpretations of Computer-Generated Traditional Music, by John Hughes

Recorded on Dec. 9, 2017

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Added by Toby Harris

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Double bassist John Hughes interprets five tunes generated by folk-rnn (v2) at a concert at the University of Hamburg, Dec. 9 2017.

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The Machine Folk Session is a project funded by the UK Arts and Humanities Research Council, grant no. AH/R004706/1: "Engaging three user communities with applications and outcomes of computational music creativity". See also: folk-rnn, where you can generate folk tunes with a recurrent neural network.

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