Analogue Modelling Versus Digital Plugins

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Abstract

This study examines the perceptual differences between music mixed with paid analogue-modelling plugins and free non-modelling plugins, within the context of typical music consumption. To explore this, a blind AB test was conducted and featured in a YouTube video, with uncompressed 24-bit, 44.1 kHz audio files additionally provided via a link in the pinned comment. 514 participants assessed two mix versions of a song. One version, the “analogue mix,” utilised 49 instances of paid analogue-modelling plugins from reputable manufacturers, while the other, the “digital mix,” was matched to the first using only free non-modelling plugins. The primary objective was to determine whether listeners could accurately identify the analogue mix and if there was a preference for it. Statistical analysis of survey responses revealed a significant tendency to misidentify the analogue mix (p < 0.004) and no statistically significant preference for the analogue mix (p > 0.58).

Professional DACs are transparent, even if most people disagree

This website uses no cookies directly. However, embedded YouTube videos may set cookies and process personal data once played. By interacting with the video, you consent to YouTube’s data processing. See YouTube’s privacy policy for details.

Abstract

The ongoing debate over whether high-end digital-to-analog converters (DACs) provide audible improvements over professional-grade, moderately priced DACs remains a contentious topic within both audiophile and professional audio communities. This study examines claims of perceived sonic differences between DACs by conducting a blind listening test utilizing a loopback methodology. A music recording was played through a moderately priced DAC (TC Electronic BMC-2) and rerecorded (using a MOTU 24Ai) to create a loopback signal. Participants (N = 1,367) attempted to detect differences between the original and loopback signals via the YouTube platform. Statistical analysis of responses found no evidence that listeners could reliably distinguish between the original recording and its loopback version (p < 10⁻⁹).

In contrast, an analysis of over 1000 YouTube comments using a large language model (LLM) revealed that 54.4% of commenters on the same video believed DACs exhibit unique sonic characteristics, often attributing differences to factors such as the analog output stage, power supply design, and implementation details. Many comments exhibited patterns of informational social influence, suggesting a reinforcement of beliefs independent of empirical verification. The results highlight a disconnect between objective listening test data and subjective listener perceptions, likely driven by marketing influences, cognitive biases, and group dynamics. This study reinforces the conclusion that well-engineered DACs achieve transparency in single-generation listening scenarios, with no demonstrable auditory benefit from higher-priced alternatives.