The mixing stage in music production involves a complex set of interdependent technical and creative decisions aimed at achieving a coherent and industry-level result. Intelligent Music Production (IMP) is an emerging research area that integrates Artificial Intelligence techniques into music creation and post-production processes, spanning from composition to mastering. Within this context, Answer Set Programming (ASP), a declarative paradigm from Knowledge Representation and Reasoning, has proven effective for modeling and solving complex optimization problems. This article presents frmixerr, an ASP-based intelligent system designed to optimize the mixing process by automatically generating balanced mixes. The system formulates mixing as a combinatorial optimization problem and evaluates candidate solutions against a reference spectral profile. To assess its performance, a subjective listening test was conducted comparing mixes generated by frmixerrwith mixes produced by human engineers with varying levels of professional experience. The results indicate no significant differences in perceived quality between frmixerrmix and those created by professionals, suggesting that ASP constitutes a viable approach for intelligent assistance in music mixing.
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