Intelligent Audio Production Strategies Informed by Best Practices
Pedro Pestaña, Joshua D. Reiss · Queen Mary Research Online (Queen Mary University of London) · 2014
The main focus of this article is to explore and investigate the fundamental constraints that should be at the basis of algorithm development in intelligent audio production systems. Through mix analysis and grounded theory strategies, a best-practices framework on the craft of mixing is sought out. Findings, while not to be taken as dogmatic, give a clear indication of preferred implementation strategies, and show what still needs to be done to fully understand the technical choices that audio mixing has incorporated throughout its history. 1. CONTEXT The last five years have witnessed blooming of research in the field of automatic mixing [1], powered by cross-adaptive digital audio algorithms [2]. Most of the devel-oped strategies, while showing promising results, have mainly relied on the author’s experience, or on literature review where literature is exiguous. We argue that a more thorough exploration on what the premises are is essen-