B3 Non-refereed article in a conference publication

Cheese identification based on feature extraction from rubbing sounds;




AuthorsNurkkala, Elina; Czedik-Eysenberg, Isabella; Reuter, Christoph; Hopia, Anu; Postema, Michiel

Conference nameDAGA

PublisherDeutsche Gesellschaft für Akustik

Publication year2026

Book title Fortschritte der Akustik - DAGA 2026

Article number387

First page 1130

Last page1132

ISBN978-3-939296-24-9

DOIhttps://doi.org/10.71568/daga2026.387

Publication's open availability at the time of reportingOpen Access

Publication channel's open availability Open Access publication channel

Web address https://doi.org/10.71568/daga2026.387


Abstract

When biting and chewing food, the sounds produced convey emotions that help us to identify what we are eating and to evaluate its quality. Although extensive scientific attention has been paid to fruits, vegetables, and crisps, only a sparse number of scientific manuscripts has been dedicated to cheese acoustics, despite the notorious loudness of string cheeses. The purpose of this study was to find quantitative acoustic parameters to discriminate cheese types from rubbing. Audible audio clips were collected from rubbing leipäjuusto, mozzarella, and Gouda cheese samples with a wetted blade in a controlled low-noise environment. Twelve hundred clips were processed automatically to extract psychoacoustic features which included harmonic loudness, nontempered energy ratio, and dynamic complexity. It was found that, based on psychoacoustic features, cheese types can be discriminated with near-perfect accuracy. In addition, from a psychoacoustic point of view, leipäjuusto can be classified as “annoying yet interesting”.



Last updated on 18/08/2026 11:50:14 AM