Information retrieval and machine learning have grown to the point of playing a leading role in all aspects of sound analysis. The role of information retrieval and machine learning in the analysis of vibrational and acoustic properties of musical instruments is a more recent development. In this article, researchers offer an overview on methodologies for vibrational, acoustic and timbral analysis, based on machine intelligence. They discuss some challenges that are emerging and will have to be faced in the future to make information retrieval and machine learning an integral part of the analysis process in musical acoustics. They also demonstrate that indicators based on averaged cross-correlations over a set of noisy acquisitions can offer a reliable technique for acquiring vibrational data with low-cost equipment and lay the foundations for fair comparisons between instruments and style classification starting from vibration.

Audio information retrieval and musical acoustics

Olivieri Marco;Malvermi Raffaele;Pezzoli Mirco;Zanoni Massimiliano;Gonzalez Sebastian;Antonacci Fabio;Sarti Augusto
2021

Abstract

Information retrieval and machine learning have grown to the point of playing a leading role in all aspects of sound analysis. The role of information retrieval and machine learning in the analysis of vibrational and acoustic properties of musical instruments is a more recent development. In this article, researchers offer an overview on methodologies for vibrational, acoustic and timbral analysis, based on machine intelligence. They discuss some challenges that are emerging and will have to be faced in the future to make information retrieval and machine learning an integral part of the analysis process in musical acoustics. They also demonstrate that indicators based on averaged cross-correlations over a set of noisy acquisitions can offer a reliable technique for acquiring vibrational data with low-cost equipment and lay the foundations for fair comparisons between instruments and style classification starting from vibration.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1189118
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