WE3.SC2.2
Feature comparison for classification of Kaustinen fiddle playing style from archived recordings using deep learning
Henna Tahvanainen, University of Bologna, Italy; Tuomas Ylönen, Turku University of Applied Sciences, Finland; Outi Valo, University of the Arts Helsinki, Finland
Session:
WE3.SC2: Audio Signal Processing for Cultural Heritage Analysis and Preservation Lecture
Track:
Special Sessions
Location:
Saint Clair 2
Presentation Time:
Wed, 28 Aug, 16:30 - 16:50 France Time (UTC +1)
Session Chair:
Toon van Waterschoot, KU Leuven
Presentation
Discussion
Resources
No resources available.
Session WE3.SC2
WE3.SC2.1: STEELPAN SYNTHESIS AND INTANGIBLE CULTURAL HERITAGE
Randall Ali, University of Surrey, United Kingdom; Bryan Khan, University of the West Indies, Trinidad and Tobago
WE3.SC2.2: Feature comparison for classification of Kaustinen fiddle playing style from archived recordings using deep learning
Henna Tahvanainen, University of Bologna, Italy; Tuomas Ylönen, Turku University of Applied Sciences, Finland; Outi Valo, University of the Arts Helsinki, Finland
WE3.SC2.3: Features vs Bands: Statistical analysis between design features and spectral power for a set of culturally relevant violins
Sebastian Gonzalez, Raffaele Malvermi, Politecnico di Milano, Italy; Mary Jane Kwan, Sam Zygmuntowicz, Sam Zygmuntowicz Violins, United States; Fabio Antonacci, Augusto Sarti, Politecnico di Milano, Italy
WE3.SC2.4: LOW-RANK MULTI-CHANNEL FAST CONVOLUTION FOR REAL-TIME AURALIZATION OF CHURCH ACOUSTICS
Hannes Rosseel, Martin Jälmby, Toon van Waterschoot, KU Leuven, Belgium