first presentation williamjens
TRANSCRIPT
Table Selecta
Jens Pelgrims
William De Keyzer
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
Who are we
• Jens Pelgrims and William De Keyzer
• Master of science:
– Master in de toegepaste informatica
• Mentor: Gonzalo Alberto Parra Chico
Context
• Music
• Public Location
• Smartphone
• Tabletop
• Computer
Why we chose this subject
• Music
• Nightlife
• We would use it
• Smartphone => Android
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
Problem
• DJ isn’t able to connect with crowd
• People don’t feel involved in music choice
• Music is just background “noise”
• Bars don’t really care about music, they just want profits
– People having fun tend to consume more
Problem
• People don’t want same things on party as in bar
• No DJ in bar
• Different context
– party
– bar
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
Research Questions
• Could we improve the atmosphere in a public space by allowing the crowd to influence the music?
• Can this be done with an app on a mobile phone?
• How will we make this communication?
• Would it be good to give (partial) control of the music in a public space to the users?
• Do we need some form of control?
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
Objectives
• Provide users the option to “aid” in music choice let their voice be heard
• Provide DJ’s with better ways to connect with the crowd
• Specifically– Information about the crowd’s preferences
• Exact statistics about genres and how many users like it
– Requests• The ability to request songs• The ability to view requested songs
– Voting• Votes can be made by the DJ• Users can then vote on it
Two versions
• Party
– DJ has control, but wants interact with the crowd
• Bar/Home
– Computer with music database
– Users have more control
– Autonomously
Version 1: Party
• App for smartphone
• Not central (overwhelming activity) at party
• Users feel involved
• DJ has control nevertheless
Version 2: Bar/Home
• App for smartphone
• Computer plays music, works autonomously
• Users have more control
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
Music Listening personal
• People listen alone
• Loan CD
• Tell others about artists/songs
- Seeburger, D.2012, The Sound of Music: Sharing Song Selections between Collocated Strangers in Public Urban Places
- Baur, D.2012,Listening Factors: A Large-Scale Principal Components Analysis of Long-Term Music Listening Histories
- Camurri, D.2008,Active and Personalized Experience of Sound and Music Content
Music Listening sharing
• People want to share what they like
– (Facebook/Twitter)
• Collaborative listening is complex
- Purgina, D.2013,An Approach for Developing a Mobile Accessed Music Search Integration Platform
- Chao, D.2005Adaptive Radio: Achieving Consensus Using Negative Preferences
- Cunningham, D.2009,Exploring Soial Music Behavior: an Investigation of Music Selection at Parties
- Crossen, D.2002,Flytrap: Intelligent Group Music Recommendation
- Liu, D,2008,Social Playlist: Enabling Touch Points and Enriching Ongoing Relationships Through Collaborative Mobile Music Listening
Collaborative Listening
• Online profiles
• Dedicated computer
• Tabletop
• Shared screen
• Seperate decives
• Online playlist
Online profile
Dedicated Computer
• Computer in different room
• Leave your group
- Sprague, D. 2008,Music Selection using the PartyVote Democratic Jukebox
Tabletop
- Stavness , D,2005,The MUSICtable: A Map-based Ubiquitous system for Social Interaction with a digital music Collection
- F. Julia, D,2009,SongExplorer: a tabletop application for exploring large collections of songs
Shared Screen
- Cunningham, D,2009,Exploring social music behaviour: An investigation of music selection at parties
- Kukka, D,2009,UbIRockMachine: A Multimodel Music Voting Service for Shared Urban Spaces
Seperate Device
- Lipson, D,2004,Jukola: Democratic Music Choice in a Public Space
Online playlistTuneTug
http://www.tunetug.com
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
Party
• Have a good time
• Know which song is played
• Request songs
• Ask for other genre
Bar
• Have conversation
• Listen to music in background
• Ask friends which song it is
• On facebook/foursquare/... with smartphone
• Make request at barkeeper
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
Functionalities
• App-side– Give preferences– Vote– Make request
• Server-side– View preferences– Start vote– View requests
• Big screen– Dashboard
First Paper Prototype
Dashboard
Feedback
• SUS: 84%
• Dashboard has more potential
• Request screen not clear enough
• More feedback on the app
Second Prototype
Votes
Votes3 new screens instead of 1
Requests
Requests2 screens instead of 1
Digital Prototype
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
Planning
• December: Continue with digital prototype
• January: Exams + digital prototype + writing
• February: Finish digital prototype + start testing
• March: Further testing of digital prototype + make adaptations if necessary+ test second digital prototype
• April: Test second digital prototype (finish)+ last adaptations + writing
• May: Writing
Planning – Future Questions
• Is server-client structure ideal?
• Is working on the same LAN good?
• Would autocomplete work best with sending data to server, or with local data?
• Will the app be responsive enough?
• How can we minimize the communication between the server and app
• Introduction
• Problem
• Research question
• Objectives
• Literature study
• Real-life observations
• App
• Planning
• Workload
Workload
Total hours worked: 274Expected score: 13/20
Thank you for listening
• Any questions?