How Machine Learning Contributes to Solve Acoustical Problems

Marie A. Roch; Peter Gerstoft; Bożena Kostek; Zoi-Heleni Michalopoulou

doi:10.1121/at.2021.17.4.48

How Machine Learning Contributes to Solve Acoustical Problems

Abstract

Machine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task (Schedl et al., 2014). Alternatively, we may be interested in an exploratory analysis, such as discovering relationships between animal-produced sounds and potential call categories that may carry signaling information (e.g. Sainburg et al., 2020). Machine learning can be used to discover information about the physical world such as determining the distance to a source based on pressure levels in a vertical line array (Niu et al., 2017) or solving inversion problems to find geoacoustic parameters of a seabed (Benson et al., 2000). In this article, we provide a gentle, and hopefully intuitive introduction to machine learning with only a limited number of examples and techniques. For readers who wish to read a more detailed introduction, we recommend the recently published review by Bianco et al. (2019) that focuses on machine learning and acoustics, or one of the many excellent book-length treatments of machine learning (e.g. Bishop, 2006; Goodfellow et al., 2016; Hastie et al., 2009).

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Authors (4)

Marie A. Roch Prof.
Peter Gerstoft Prof.
Bożena Kostek prof. dr hab. inż.
Zoi-Heleni Michalopoulou Prof.

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DOI:: Digital Object Identifier (open in new tab) 10.1121/AT.2021.17.4.48
License: Copyright (2021 Acoustical Society of America)

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Category:

Articles

Type:

artykuły w czasopismach

Published in:

Journal of the Acoustical Society of America no. 17, pages 48 - 57,
ISSN: 0001-4966

Language:

English

Publication year:

2021

Bibliographic description:

Roch M. A., Gerstoft P., Kostek B., Michalopoulou Z.: How Machine Learning Contributes to Solve Acoustical Problems// Journal of the Acoustical Society of America -Vol. 17,iss. 4 (2021), s.48-57

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