Personalized Visual-Interactive Music Classification
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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
We present an interactive visual music classification tool that will allow users to automatically structure music collections in a personalized way. With our approach, users play an active role in an iterative process of building classification models, using different interactive interfaces for labeling songs. The interactive tool conflates interfaces for the detailed analysis at different granularities, i.e., audio features, music songs, as well as classification results at a glance. Interactive labeling is provided with three complementary interfaces, combining model-centered and human-centered labeling-support principles. A clean visual design of the individual interfaces depicts complex model characteristics for experts, and indicates our work-inprogress towards the abilities of non-experts. The result of a preliminary usage scenario shows that, with our system, hardly any knowledge about machine learning is needed to create classification models of high accuracy with less than 50 labels.
Description
@inproceedings{10.2312:eurova.20181109,
booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
editor = {Christian Tominski and Tatiana von Landesberger},
title = {{Personalized Visual-Interactive Music Classification}},
author = {Ritter, Christian and Altenhofen, Christian and Zeppelzauer, Matthias and Kuijper, Arjan and Schreck, Tobias and Bernard, Jürgen},
year = {2018},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-064-2},
DOI = {10.2312/eurova.20181109}
}