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Elevator AnnotatorLocal Crowdsourcing on Audio Annotation for Netherlands Institute for Sound and Vision
Anggarda Prameswari [email protected]
Supervisor: Victor de BoerDaily Supervisor: Themistoklis Karavellas
Elevator AnnotatorWhat is it about?
▷ The rise of crowdsourcing practice in the community→Crowdsourcing is seen to be an attractive solution to acquire annotations cheaply and quickly
▷ Local crowdsourcing:→ Participants do the given tasks on site while overcoming challenges and influences posed by physical environment→ Example: Local visitors in a museum help annotate the painting collections
What about audio collections?
Background
Audio file
▷ An audio file consists of multiple information (metadata)▷ There are many musical instruments involved in a song▷ In a fragment of seconds there will different instrument
playing dominantly
Case study
▷ Netherlands Institute for Sound and Vision→ Largest audiovisual archive in the Netherlands→ To collect and preserve audiovisual heritage→Make it available to as many users as possible
▷ How? → Enriching the audio collection’s content by having additional information of the instruments→Make use of local crowdsourcing with pervasive computing→ Experimenting in an elevator (Why?)
→Used frequently, people will mostly be idle, thus ideal to ask for annotation
Research Questions
“Can local crowdsourcing be used to enrich the audio collection content with improved quality?”
▷ What are the requirements for the crowdsourced annotations according to its technical and ethical aspects?
▷ How do different physical locations of the local crowdsourcing affect the result?
▷ How do different type of user interactions of the local crowdsourcing affect the result?
ApproachHow will it be carried out?
Approach(February - March)
▷ Implementation →Develop a system using Raspberry Pi as the platform
Approach(April - May)
▷ Experiments → Locations: Offers different institutional properties
→User interfaces: Offers different feedback to the user
▷ Evaluation →Accuracy of musical instrument identification→Willingness of crowd to participate→ Participation statistic
▷ Result→ Source codes with the prototype→Comprehensive report of evaluation
Approach(continuously - June)
Thanks!Any questions?
