Difference between revisions of "GuitarFace"

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(GuitarFace)
(GuitarFace)
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== GuitarFace ==
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== By Roshan Vid and Gina Collecchia ==
 
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'''subtitle'''
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By Roshan Vid and Gina Collecchia
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'''Goals'''
 
'''Goals'''

Revision as of 18:11, 5 November 2013

By Roshan Vid and Gina Collecchia

Goals

To predict and identify virtuosity in rock guitar solos by analyzing MIDI data with supervised learning (SVM).

Rock music is one of the largest genres of music, but there are individual artists who stand out as titans in the genre. Led Zeppelin, The Doors, and Jimi Hendrix are just a few examples of bands that truly convey masterfulness in the genre. The guitar is frequently given the spotlight of a rock band. Rock and roll has some core instruments: the electric guitar, bass, drums, and voice. We could compare it to other genres on a basis of instrumentation, and find some differentiation. For example, jazz would have a noisier distribution of instruments: perhaps a peak over drums and the trumpet, but would we see the same over the piano and guitar?

Similarly, there are other features besides instrumentation that are core to rock, and furthermore rock guitar soloing:

  • scale / key
  • timing
  • dynamic range (loudness)
  • pitch range
  • expectation (build-up and violation)
  • repetitiveness
  • non-pitched decorations
  • vibrato, bend

but that does not mean that there do not exist boundaries of what qualifies as good rock and roll. Timing, tone, creativity, and cool can all completely make or break a song.