Mood of music is one of the most intuitive criteria for listeners, thus it is used in automated systems for organizing music. This study is based on the emotional content of music and its automatic recognition and contains outcomes of a series of experiments related to building models and description of emotions in music. One-hundred-fifty-four excerpts from 10 music genres were evaluated in the listening experiments using a graphical model proposed by the authors, dedicated to the subjective evaluation of mood of music. The proposed model of mood of music was created in a Max MSP environment. Automatic mood recognition employing SOM and ANN was carried out and both methods returned results coherent with subjective evaluation.

Authors: Plewa, Magdalena; Kostek, Bozena; Bieñ, Mateusz
Affiliations: Gdansk University of Technology, Gdansk, Poland; Academy of Music in Kraków, Kraków, Poland(See document for exact affiliation information.)
AES Convention: 140 (May 2016) Paper Number: 9568
Publication Date: May 26, 2016
Subject: Live Sound Practice, Rendering, Human Factors and Interfaces

Click to purchase paper as a non-member or you can login as an AES member to see more options.

No AES members have commented on this paper yet.

Subscribe to this discussion

To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Start a discussion!

If you would like to start a discussion about this paper and are an AES member then you can login here:
Username:
Password:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.