Accelerating the Mixing Phase in Studio Recording Productions by Automatic Audio Alignment

Nicola Montecchio (1) , Arshia Cont (1)

1 Repmus - Représentations musicales

We propose a system for accelerating the mixing phase in a recording production, by making use of audio alignment techniques to automatically align multiple takes of excerpts of a music piece against a performance of the whole work. We extend the approach of our previous work, based on sequential Montecarlo inference techniques, that was targeted at real-time alignment for score/audio following. The proposed approach is capable of producing partial alignments as well as identifying relevant regions in the partial results with regards to the reference, for better integration within a studio mix workflow. The approach is evaluated using data obtained from two recording sessions of classical music pieces, and we discuss its effectiveness for reducing manual work in a production chain.

Mots clés: NA; Informatique musicale

Domaines: Langage de programmation [cs.PL]; Son [cs.SD]; Traitement du signal et de l'image [eess.SP]; Machine Learning [stat.ML]; Intelligence artificielle [cs.AI]; Théorie et langage formel [cs.FL]; Musique, musicologie et arts de la scène

Nicola Montecchio, Arshia Cont. Accelerating the Mixing Phase in Studio Recording Productions by Automatic Audio Alignment. International Symposium on Music Information Retrieval (ISMIR), Oct 2011, Miami, United States. pp.627-632. ⟨hal-01161008⟩