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ABSTRACT

We present "Herd It", a competitive, online, multi-player game that has the implicit benefit of collecting tags for music. We describe Herd It's user-centered design process and demonstrate that the game can collect both musical and social data. This data can be used to build machine learning models that automatically associate music with tags. Herd It differs from previous "games with a purpose" in that it is designed to be social: the game runs on the Facebook online social network and scoring is based on consensus between a large group of listeners - "the Herd". By presenting music in a social context, Herd It adds demographic context to the semantic music descriptions that it collects.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.3 Group and Organization Interfaces
      H.5.5 Sound and Music Computing

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems

Keywords:
auditory I/O and sound in the UI, computer audition, distributed knowledge acquisition, web-based games with a purpose