Mono compatibility is a fundamental challenge in audio production, ensuring that stereo mixes retain clarity, balance, and spectral integrity when summed to mono. Traditional stereo widening techniques often introduce phase shifts, comb filtering, and excessive decorrelation, causing perceptual loss of critical mix elements in mono playback. Diffuse Signal Processing (DiSP) is introduced as a convolution-based method that improves mono compatibility while maintaining stereo width.
This study investigates the application of DiSP to the left and right channels of a stereo mix, leveraging MATLAB-synthesized TDI responses to introduce spectrally balanced, non-destructive acoustic energy diffusion. TDI convolution is then applied to both the left and right channels of the final stereo mix.
A dataset of stereo mixes from four genres (electronic, heavy metal, orchestral, and pop/rock) was analyzed. The study evaluated phase correlation, mono-summed frequency response deviation and amount of comb filtering to quantify improvements in mono summation. Spectral plots and wavelet transforms provided objective analysis. Results demonstrated that DiSP reduced phase cancellation, significantly decreased comb filtering artifacts, and improved spectral coherence in mono playback while preserving stereo width within the original mix. Applying this process to the final left and right channels allows an engineer to mix freely without the concern of the mono mix’s compatibility.
DiSP’s convolution-based approach offers a scalable, adaptive solution for modern mixing and mastering workflows, overcoming the limitations of traditional stereo processing. Future research includes machine learning-driven adaptive DiSP, frequency-dependent processing enhancements, and expansion to spatial audio formats (5.1, 7.1, Dolby Atmos) to optimize mono downmixing. The findings confirm DiSP as a robust and perceptually transparent method for improving mono compatibility without compromising stereo imaging.
