MusicFX: An Arbiter of Group Preferences for Computer Supported Collaborative Workouts (CSCW98)
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MusicFX: An Arbiter of Group Preferences for Computer Supported Collaborative Workouts (CSCW98)

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MusicFX is an example of an active environment that uses a group preference arbitration system to allow the members of a fitness center to influence, but not directly control, the selection of music ...

MusicFX is an example of an active environment that uses a group preference arbitration system to allow the members of a fitness center to influence, but not directly control, the selection of music in that environment. The system contains a database of members' musical preferences, a badge system for determining who is working out, and a weighted random selection algorithm for selecting music to best suit the group inhabitants at any given time. MusicFX was deployed in the fitness center at Accenture Technology Park in Northbrook, IL (USA) from November 1997 through January, 2002. These slides are from the CSCW 98 presentation on the system. More info, including the CSCW 98 paper, can be found at http://interrelativity.com/joe/projects/MusicFX.html

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MusicFX: An Arbiter of Group Preferences for Computer Supported Collaborative Workouts (CSCW98) MusicFX: An Arbiter of Group Preferences for Computer Supported Collaborative Workouts (CSCW98) Presentation Transcript

  • MusicFX: An Arbiter of Group Preferences for Computer Supported Collaborative Workouts Joe McCarthy Ted Anagnost Andersen Consulting Center for Strategic Technology Research
  • Outline
    • UbiComp & Intelligent Environments
    • The MusicFX System
    • Evaluating Group Preference Arbitration
    • Future Work
  • Ubiquitous Computing
    • Proliferation of networked devices
      • phones, TVs, cam's, mic's, microwaves, refrigerators...
    • Distribution of computing resources
      • portable, wearable, embedded
    • New paradigm of computing
      • input/output ( foreground ) --> sense/respond ( background )
  • Intelligent Environments
    • “ UbiComp in a box”
      • Interconnected, cooperating devices
      • Concentrated in a small area (e.g., one room)
    • Redefining HCI
      • users --> inhabitants
  • Observation 1
    • Most UbiComp applications focus on single individuals in multiple spaces
      • Active Badge: open doors, teleporting
      • ParcTab: information access, email
    • What about multiple inhabitants in a single, shared space ?
  • Observation 2
  • Music in the Fitness Center (FX)
    • Popular in the Complaint Department
      • 25% of “feedback” focused on music
    • RSI: Repetitive Song Injury
      • 3 stations played, 91 available (DMX)
    • Squeaky Wheels
      • Vocal minority prevails over silent majority
    • Hangovers
      • This morning’s music = last night’s music
  • Four Issues for any Intelligent Environment
    • Who’s here?
    • What are they doing?
    • What are their preferences?
    • What can I do to help?
  • Four Issues for MusicFX
    • Who’s here?
      • Members who login [badge reader]
    • What are they doing?
      • Working out while listening to music
    • What are their preferences?
      • Diverse (to say the least)
    • What can I do to help?
      • Play “good” music
  • The MusicFX System
    • Database of musical preferences
    • Group Preference Arbitration algorithm
      • Group Preference Calculation
      • Candidate Identification
      • Weighted Random Selection operator
  • Music Preference Database
    • 275 fitness center members
    • 91 musical genres (DMX stations)
    • 5-point rating scale
      • +2 = I love this music
      • +1 = I like this music
      • 0 = I don’t mind this music
      • -1 = I dislike this music
      • -2 = I hate this music
  • Group Preference Arbitration
    • Group Preference Calculation
    • Candidate Identification
    • Weighted Random Selection
  • Group Preference Calculation
    • Where
    • GP i = G roup P reference for genre i
    • IP i,j = I ndividual P reference of person j for genre i
    • N = N umber of inhabitants
  • Candidate Identification
    • Sort genre list by GP i
    • Remove any undesireable genre
      • Individual Preference Filter
    • Candidates are the first M genre
      • Group Preference Filter
  • Weighted Random Selection
    • Calculate weights for candidates
    • Probabilistically select genre according to W i
  • An example
  • Environmental Events
    • Member entrance
      • Login (badge reader)
    • Member exit
      • Timeout (90 minutes)
    • Individual Preference Update
    • System Parameter Adjustment
      • Individual / Group Preference Filter, Maximum Play Time
    • Maximum Play Time Elapsed
  • The Success of MusicFX
    • Daily operation since November 1997
    • Poll results (after 6 weeks)
      •  : increased variety, having some influence
      •  : abrupt changes, occasional “bad” music
  • Evaluating Group Preference Arbitration
    • Calculate the “goodness” of MusicFX
    • Estimate the “goodness” of old scheme
    • Compare the old with the new
  • The “Goodness” of MusicFX
    • Individual Satisfaction rating ( IS )
      • Time i,j = time person j spent listening to genre i
      • IP i,j = person j ’s Individual Preference for genre i
  • The “Goodness” of MusicFX
    • Overall Satisfaction rating ( OS )
      • For all N members
  • Individual Satisfaction for all 275 FX Members
  • The “Goodness” of the Old Days
    • Three genres ( n=3 )
      • Hottest Hits, Power Hits, Dance
      • Assume each person listened to each genre 1/3 of the total time spent working out
  • Comparing the Old with the New
    • Overall Satisfaction
      • “ Old scheme”: 0.44
      • MusicFX: 0.64
        • 8% higher (statistically significant)
  • Average Individual Preferences
  • Top 10 Stations
  • MusicFX Anecdotes
    • Veto power & IPF
    • Uncommon variety
    • The Polka incident
    • The Chinese Music incident
  • The Future of MusicFX
    • Better awareness of inhabitants
    • Alternative rating/voting schemes
    • Alternative arbitration schemes
  • Individual Satisfaction after 6 months (Avg: 0.64)
  • Average Preferences after 6 months (Avg: -0.39 to -0.50)
  • Future Group Preference Applications