ValhallaShimmer is an algorithmic reverberation plugin. It is designed to produce BIG sounds, from concert halls, to the Taj Mahal, to the halls of Valhalla.
There are several reverberation modes available, to allow the user to dial in the preferred initial sound. By adjusting the Feedback, Diffusion and Size controls, the attack, sustain and decay of the reverb signal can be fine tuned. The modulation controls can be set to produce subtle mode thickening, glistening string ensemble-esque decays, and the distinctive random modulation of the older Lexicon hall algorithms. Two tone controls and the Color Mode selector allow the timbre to be adjusted from bright and glistening to a more natural dark decay, similar to that produced by air absorption in large spaces.
In addition, ValhallaShimmer has the ability to pitch shift the feedback signal. There are 3 pitch shift modes available:
- Single, where the feedback is shifted up or down by the Shift value.
- Dual, where the feedback is shifted both up and down (in parallel) by the Shift value.
- Bypass, which turns off the pitch shifting (useful for "standard" reverb sounds).
By setting the Shift amount to +12 semitones, and the Feedback to 0.5 or greater, the classic "shimmer" sound is produced, as heard on Eno / Lanois productions for U2 and others. The algorithms allow for the classic shimmer effects to be generated with ease, as well as a variety of pitch shifted, evolving ambiences.
ValhallaShimmer is the end result of several years of research, and is highly optimized:
- The core pitch shifting algorithm uses randomization to avoid the comb filtering artifacts that can be heard in simpler pitch shifters.
- The code has been optimized for SIMD processors, in order to allow the complex algorithm to run while using a small fraction of modern CPUs.
- The reverberation algorithm has been designed to work in conjunction with the pitch shifting, to allow for high levels of feedback without compromising stability.
- The algorithm works well with cascading multiple instances, both from a signal processing perspective and in terms of the low CPU consumption.