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