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and certain songs. To gather more evidence showing that the mood
pictures concept is valid and feasible for music discovery, most of the
users would then have to agree with the selected basic music/picture pairs.
To help the users to interpret the mood pictures more easily, one
design approach worth trying could be to focus more on the facial
expressions, gestures, and postures of people shown in the pictures.
Furthermore, every user could have his/her personalized playlist of songs
for each picture, with modifications that could then be shared with other
users. Another design alternative would be to allow users to contribute
their own photos as mood pictures. In this case, a playlist associated with a
given mood picture could then be populated collaboratively by the users of
the system. Other interesting topics for future research include
investigating how generic certain music/picture associations are within a
specific culture, and studying how much the animation layers can improve
how people interpret the intended feeling of the picture. In a practical
mood player application, the users themselves could add such layers on
top of the pictures.
This user study was conducted as part of a user study on six music
player prototypes. After the other prototypes have been analysed in detail,
the results should be compared against each other and used to design a
next-generation, “ultimate” visual music player UI comprising both
visualizations and textual lists.
References
AllMusic. http://www.allmusic.com. (accessed December 2012)
Casey, M., Veltcamp, R., Goto, M. Leman, M., Rhodes, C., Slaney, and M.
“Content-Based Music Information Retrieval: Current Directions and Future
Challenges.” Proceedings of the IEEE 96 , no. 4 (2008): 668-696.
Celma, Oscar. “Music Recommendation and Discovery in the Long Tail.” PhD
diss., Universitat Pompeu Fabra, 2008.
Deezer. http://www.deezer.com. (accessed December 5, 2012)
Dey, A. K. and Abowd, G. D. “Towards a Better Understanding of Context and
Context-Awareness.” Tech. Report
GIT-GVU-99-22. Atlanta: Georgia
Institute of Technology, 1999.
Dunker, P., Nowak, S., Begau, and A. Lanz, C. “Content-Based Mood
Classification for Photos and Music: A Generic Multimodal Classification
Framework and Evaluation Approach.” Paper presented at the International
Conference on Multimedia Information Retrieval, Philadelphia, USA,
September 14-18, 2008.
Ekman, Paul. Emotions Revealed - Understanding Faces and Feelings . London:
Orion Books, 2004.
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