DialogCheck

DialogCheck addresses a persistent problem in post-production: the inability to objectively assess dialog intelligibility. Mixing engineers lose perspective after repeated exposure to the same material, making it nearly impossible to evaluate whether a vocal performance will remain clear to a first-time listener. This plugin quantifies that missing variable through dual AI neural networks trained on speech intelligibility data, providing real-time measurement rather than guesswork.

The plugin operates across immersive formats up to 7.1.4, processing dialog in context within your full mix rather than in isolation. Its interface displays multiple metrics simultaneously: momentary clarity for immediate feedback, median clarity across a passage, and user-definable percentile readouts that reveal intelligibility at specific distribution points. A timecode-locked history graph preserves measurements throughout your session, and a real-time bar meter offers instantaneous visual reference while working.

DialogCheck belongs in any facility handling dialog-heavy content. Post-production engineers mixing film and television will find it invaluable for objective verification before delivery. Streaming content creators preparing material for various playback environments benefit from its percentile analysis, which predicts how dialogue will perform across different listening conditions and audience hearing acuity.

The underlying approach leverages machine learning trained on perceptual data rather than simple spectral analysis, distinguishing it from earlier algorithmic intelligibility tools. While not a substitute for critical listening, DialogCheck restores objectivity to a decision that fatigue and habituation have obscured. For professionals mixing high-stakes dialog, the clarity it provides justifies its place in the toolchain.