Difference between revisions of "Talk:Audio Music Mood Classification"

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A good solution might be a tradeoff between psychological studies and social context information we can grab from real applications and large online communities (music websites with mood tags from the users)
 
A good solution might be a tradeoff between psychological studies and social context information we can grab from real applications and large online communities (music websites with mood tags from the users)
 
--[[User:Claurier|Claurier]] 09:17, 15 February 2007 (CST)
 
--[[User:Claurier|Claurier]] 09:17, 15 February 2007 (CST)
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I agree this is a difficult task, and MIREX is the best place to handle difficult tasks because it gathers the attention and strength of the whole MIR community. As this is the first time for mood classification, I like your idea of making it simpler by setting up fewer mood categories.
 
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Juslin's categories have good musicpsychological roots, but he and Laukka confessed their model took a musican's stand and ignored the socical context of music listening. (Juslin, P. N., & Laukka, P. (2004). Expression, perception, and induction of musical emotions: A review and a questionnaire study of everyday listening. Journal of New Music Research, 33(3), 217-238. )
 
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Existing music websites like AMG are right in the social context. So this is their advantage. AMG is a mess indeed, so I like MoodLogic more. MoodLogic has only 6 categories, but we are not sure about it without knowing how they came up with the 6 labels.
 

Latest revision as of 22:43, 18 February 2007

Looking at the literature, we can conclude that there is no standard in mood taxonomy. Another conclusion is that using many categories gives bad results in the automatic classification, that might be because even humans between them don't have a good agreement. Many categories makes it too overlapped and subjective. But anyway psychological studies have some results about agreement (see Juslin for example). A good solution might be a tradeoff between psychological studies and social context information we can grab from real applications and large online communities (music websites with mood tags from the users) --Claurier 09:17, 15 February 2007 (CST)

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