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Automatic Music Production System Employing Probabilistic Expert Systems

An automatic music production system based on expert audio engineering knowledge is proposed. An expert system based on a probabilistic graphical model is employed to embed professional audio engineering knowledge and infer automatic production decisions based on musical information extracted from audio files. The production pattern, which is represented as probabilistic graphical model, can be ‘learned’ from the operation data of a human audio engineer or manually constructed from domain knowledge. The authors also discuss the real-time implementation of the proposed automatic production system for live mixing application scenarios. Musical event alignment and prediction algorithms are introduced to improve the time synchronization performance of our production model. The authors conclude with performance evaluations and a brief summary.

Authors: Bocko, Gregory; Bocko, Mark F.; Headlam, Dave; Lundberg, Justin; Ren, Gang
Affiliations: Dept. of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA; Dept. of Music Theory, University of Rochester, Rochester, NY, USA(See document for exact affiliation information.)
AES Convention:129 (November 2010) Paper Number:8255 Import into BibTeX
Subject:Signal Analysis and Synthesis

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