Now it is the library that can be connected to everything in the Python world.Processing speed and accuracy have been increased.Our own open source brickwall limiter was implemented for it.Completely rewritten in Python 3, based on open source tech stack (no more MATLAB).You can do everything as you want! Because of Your References, Your Rules.™ (just a little nostalgic note) □ĭifferences from the previous major version:.You can find new aspects of your sound in experiments.You can make all the tracks on your new album sound the same very quickly.You can make your music instantly sound like your favorite artist's music.So Matchering 2.0 will make your song sound the way you want! It opens up a wide range of opportunities: You can try out Matchering yourself without having to install it, thanks to the hosting provided by Moises.ai. Our algorithm matches both of these tracks and provides you the mastered TARGET track with the same RMS, FR, peak amplitude and stereo width as the REFERENCE track has. REFERENCE (another track, like some kind of "wet" popular song, you want your target to sound like it). ![]() TARGET (the track you want to master, you want it to sound like the reference).It follows a simple idea - you take TWO audio files and feed them into Matchering: Matchering 2.0 is a novel Containerized Web Application and Python Library for audio matching and mastering.
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