During the research phase of Addictive Trigger, users around the world reported that accurate hit detection is absolutely critical when using drum replacement plugins.

Unfortunately, existing triggering technologies tend to have shortcomings that require lots of manual tweaking and correction.

We endeavor to make products that are better than what is currently available, and we ended up creating an entirely new method for drum hit detection called Audio Fingerprint.

Our new system uses FFT analysis to accurately identify drum sounds even if there is a lot of mic bleed or background noise in the source material. It’s fast, it’s accurate, and we think it’ll change the way you work with live-recorded drums.

Typical drum replacement tools rely on rudimentary filtering and transient detection, resulting in many false triggers and missed hits. Audio Fingerprint solves this problem by using a novel FFT-based matching system.

It is so accurate, it usually has no trouble detecting lightly played ghost notes from background noise while simultaneously rejecting mic bleed and other unwanted sounds.

In addition to detecting low level ghost notes with great accuracy, our Audio Fingerprint system can also differentiate between different stroke types that are played at similar velocities (for example, sidestick and open snare hits).

This lets Addictive Trigger play back the correct articulations of samples, even if the incoming source material has different kinds of drum hits with similar peak levels.