"Tasting" sounds by A.I. Sommelier - Unsupervised machine learning of wine evaluation applied for sound quality evaluation

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributed

Contributors

Abstract

Wine produced countries in European Union categorize quality of wine as three classes by subjective judgements (called as "Appellation" in French) like taste, land of producer, type of grape seed and so on. In order to evaluate those wine quality, unsupervised machine learning with measured optical and chemical data of wine enables to categorize those 3 subjective classes at high accuracies. With those "A.I. Sommelier" techniques, vacuum cleaner sounds are categorized with psychoacoustic parameters and then modeling by image recognition AI of sFFT images correlate with annoyance rating at high rate. Although unsupervised machine learning technique is uncommon, it shows unsupervised machine learning technique is useful for sound quality evaluation

Details

Original languageEnglish
Title of host publication2024 INTER-NOISE and NOISE-CON Congress and Conference Proceedings
Pages3223-3233
Number of pages11
Volume270
Publication statusPublished - 2024
Peer-reviewedNo

Publication series

SeriesINTER-NOISE and NOISE-CON Congress and Conference Proceedings
ISSN0736-2935

External IDs

Mendeley bad69351-1e8c-34e9-ab40-3e82c418ee0b