Open Research - Background Reading
The story so far - this is an experiment in 'open research' -
I'm going to blog my research on a particular topic. In this post, I'm
outlining some of the background reading for this paper. Suggestions are
welcome
Table of Contents
Updates
- 6/10/2008 - Added references suggested by Elias
Music Seeking Behaviors in Music
Note that many User Oriented papers from the ISMIR community focus on specific tasks such as finding a known song or organizing a personal music collection. I'm looking for papers that focus on user aspects of music exploration and discovery, so any suggestions will be appreciated. Current resources are:- Net, Blogs and Rock 'n' Roll - a book that profiles the 4 listener types (savants, engaged, casual and indifferent)
- Fabbri, F. (1999). Browsing Music Spaces: Categories And The Musical Mind. Paper presented at the 3rd Triennial British Musicological Societies’ Conference.
- Kim, J. & Belkin, N. J. (2002). Categories of music description and search terms and phrases used by non-music experts. Proceedings of the Third International Symposium on Music Information Retrieval, 209-214.
- Laplante, A. & Downie, J. S. (2006). Everyday life music information-seeking behaviour of young adults. Proceedings of the 7th International Conference on Music Information Retrieval: ISMIR 2006.
- Lee, J. & Downie, J. S. (2004). Survey Of Music Information Needs, Uses, And Seeking Behaviours: Preliminary Findings. Proceedings of the 5th International Conference on Music Information Retrieval: ISMIR 2004, 441-446.
- Vignoli, F. (2004). Digital music interaction concepts: A user study. Proceedings of the 5th International Conference on Music Information Retrieval.
- Sally Jo Cunningham, David Bainbridge, Annette Falconer: 'More of an Art than a Science': Supporting the Creation of Playlists and Mixes. ISMIR 2006: 240-245
- Sally Jo Cunningham, David Bainbridge, Finding new music: a diary study of everyday encounters with novel songs".
- Hypemachine Survey:
Thanks to Jin Ha Lee for her excellent list of resources on Users Aspects in MIR
Genre
- Aucouturier, J.J & Pachet, F. (2003) Representing Musical Genre: A State of the Art. Journal of new Music Research.
- McKay, C. & Fuinaga, I. (2006) Musical genre classification: is it worth pursing and how can it be. Proceedings of the 7th International Conference on Music Information Retrieval
- Jeremy Reed and Chin-Hui Lee: "A Study on Attribute-Based Taxonomy for Music Information Retrieval"
somewhat random pointers to broaden the scope a bit ;-)
* Cunningham et al:
Sally Jo Cunningham, David Bainbridge, Annette Falconer: 'More of an Art than a Science': Supporting the Creation of Playlists and Mixes. ISMIR 2006: 240-245
From the abstract:
"This paper presents an analysis of how people construct
playlists and mixes. Interviews with practitioners and
postings made to a web site are analyzed using a grounded
theory approach to extract themes and categorizations. [...]"
http://ismir2006.ismir.net/PAPERS/ISMIR0685_Paper.pdf
The paper contains interesting stats such as the typical themes of playlist (in the published results 75% were not artist/genre/style related).
In the conclusions the authors write:
"[...] applications with more interactive browsing facilities and more extensive browsing structures would both make it easier to locate candidate songs and add to the individual’s pleasure of possession of the personal collection. [...]"
Btw, at ISMIR 2007 Cunningham and Bainbridge presented another related paper: "Finding new music: a diary study of everyday encounters with novel songs".
http://researchbank.swinburne.edu.au:8080/vital/access/manager/Repository/swin:6211
* Surveys and results published on Hypemachine's blog:
For example:
http://blog.hypem.com/2007/07/hype-survey-results-how-do-you-discover-music/
* Genre:
Jeremy Reed and Chin-Hui Lee: "A Study on Attribute-Based Taxonomy for Music Information Retrieval"
Pointing to alternatives to genre:
"Our experimental results demonstrate that [labels based on acoustic information] are meaningful and classifiers based on these labels achieve similar or better results than those designed with existing genre based labels."
There was also some interesting work on mood presented at ISMIR'07. For example: Xiao Hu, J. Stephen Downie: Exploring mood metadata: relationships with genre, artists and usage metadata.
Posted by elias on June 09, 2008 at 04:16 AM EDT #