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SPL BiG
Plugin Alliance

SPL BiG

Stereo & Imaging
$51.00
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Lowest ever: $50.00
90 day history
$0$25$50$75$10021 Apr14 May8 Jul
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On sale 0% of the last 90 days
Lowest tracked price: $50.00
Highest tracked price: $51.00
Rarely discounted and currently at its lowest tracked price - a genuinely good time to buy.
About

Product Overview

SPL BiG is a stereo image processor that addresses a fundamental problem in width enhancement: phase coherence. Developed by SPL and Brainworx, the plugin uses a proprietary filtering network that widens stereo content without introducing the phase cancellations and mono-sum artifacts that plague traditional M/S processors and basic stereo widening tools.

The signal path employs a unique combining method that isolates frequency ranges, allowing independent control over which elements get expanded. Three parameters handle the heavy lifting: Range selects the processing window, Stage adjusts filter slope and bandwidth to push elements forward or back in the mix, and Bigness acts as a blend control between processed and unprocessed signals. This elegant control set belies genuine sophistication underneath.

The sonic character leans toward transparent enhancement when used conservatively, though the plugin rewards aggressive settings with a distinctly colored, analog-influenced character that adds presence and dimension. The zero-phase architecture means you can push width aggressively on full mixes or individual tracks without worrying about collapsing to mono or introducing artifacts at the summing stage.

BiG is most valuable for mix engineers working with compressed delivery chains who need reliable width that survives format conversion. It's equally useful for producers seeking dimensional enhancement on keyboards, vocals, or drums without phase artifacts. The 2024 TEC Award recognition reflects genuine utility rather than novelty. While specialized tools exist for specific stereo applications, BiG's phase-coherent approach and straightforward interface make it a practical alternative to more complex spatial processors, particularly for mixing contexts where translation matters.

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