SocialFX: Studying a crowdsourced folksonomy of audio effects terms

Taylor Zheng, Prem Seetharaman, Bryan A Pardo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations


We present the analysis of crowdsourced studies into how a population of Amazon Mechanical Turk Workers describe three commonly used audio effiects: equalization, reverberation, and dynamic range compression. We find three categories of words used to describe audio: ones that are generally used across effiects, ones that tend towards a single effect, and ones that are exclusive to a single effect. We present select examples from these categories. We visualize and present an analysis of the shared descriptor space between audio effiects. Data on the strength of association between words and effiects is made available online for a set of 4297 words drawn from 1233 unique users for three effiects (equalization, reverberation, compression). This dataset is an important step towards implementing of an end-to-end language-based audio production system, in which a user describes a creative goal, as they would to a professional audio engineer, and the system picks which audio effect to apply, as well as the setting of the audio effect.

Original languageEnglish (US)
Title of host publicationMM 2016 - Proceedings of the 2016 ACM Multimedia Conference
PublisherAssociation for Computing Machinery, Inc
Number of pages5
ISBN (Electronic)9781450336031
StatePublished - Oct 1 2016
Event24th ACM Multimedia Conference, MM 2016 - Amsterdam, United Kingdom
Duration: Oct 15 2016Oct 19 2016

Publication series

NameMM 2016 - Proceedings of the 2016 ACM Multimedia Conference


Other24th ACM Multimedia Conference, MM 2016
Country/TerritoryUnited Kingdom


  • Audio engineering
  • Compression
  • Crowdsourcing
  • Effects processing
  • Equalization
  • Interfaces
  • Reverberation
  • Signal processing
  • Vocabulary

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Software


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