Surfkiss

Surfkiss

Regular price
$19 USD
Sale price
$19 USD
Regular price
$19 USD
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$9 intro price until November 24, 2023.

The same guitar as our Snowkiss Guitar library, restrung and sampled again, this time with a focus on an even wider variety of unusual techniques. In the end, the keyswitches take up more than two octaves. Though strung with heavier flatwound strings similar to those used by surf musicians in the early 1960s and featuring a complete set of normal techniques for normal styles, it also goes into no wave noise and prepared guitar territory.

Does anybody need guitar samples with a clothespin attached to the string above the one being plucked, so it bounces when a note is played, sampled with two velocity layers and four round robins? Perhaps - it certainly is more convenient to switch between that and another keyswitch than it is to set this stuff up in real life.

Walkthrough video below. Please see the Media section to the left for demo tracks. "A Gallery Of Failure" uses both Surfkiss and "real world" hardware guitar, the others are all Surfkiss for the guitar parts. 

Over 7300 samples and 3.7 GB.

  • Up to four velocity layers
  • Two to four round robins
  • Ordinary picking, picking near the bridge, hammer-ons and pull-offs
  • Three types of muting: ghost notes, palm muting, palm-muted ghost notes, and ghost notes picked near the bridge
  • Two types of harmonics
  • Three types of slides
  • Fingering noises
  • Picking behind the bridge
  • Tremolo mode for ordinary picking, picking near the bridge, and behind the bridge
  • Pick stabs with six stab locations, body punches, spoon rubs and spoon bounces, using a bottle as a pick
  • Prepared guitar techniques: binder clip, clothespin, and paper in two different locations
  • Three different types of vibrato, plus humanization
  • Two types of release noises
  • Feedback
  • Doubletracking mode
  • Random technique patches
  • Separate pad instrument with additional sympathetic resonance samples

Requires the free Plogue Sforzando sampler, which works on 64-bit Windows and Mac systems, 4 GB RAM, and an SSD.