A proposal and evaluation of new timbre visualisation methods for audio sample browsers

TL;DR

This paper introduces new timbre visualization methods for audio sample browsers, demonstrating that shape-based labels significantly enhance user search performance in large sound libraries.

Contribution

It proposes novel perceptual-based textural labels and positioning methods for timbre visualization, with an empirical evaluation of their effectiveness.

Findings

Shape labels improve search accuracy

Color and texture have minimal impact

In-person and online results are comparable

Abstract

Searching through vast libraries of sound samples can be a daunting and time-consuming task. Modern audio sample browsers use mappings between acoustic properties and visual attributes to visually differentiate displayed items. There are few studies focused on how well these mappings help users search for a specific sample. We propose new methods for generating textural labels and positioning samples based on perceptual representations of timbre. We perform a series of studies to evaluate the benefits of using shape, color or texture as labels in a known-item search task. We describe the motivation and implementation of the study, and present an in-depth analysis of results. We find that shape significantly improves task performance, while color and texture have little effect. We also compare results between in-person and online participants and propose research directions for further studies.