TY - GEN
T1 - A context-based emotion-analyzer for teaching tonality in music courses
AU - Ichinose, Aya
AU - Kurabayashi, Shuichi
AU - Kiyoki, Yasushi
PY - 2011/12/1
Y1 - 2011/12/1
N2 - This paper presents a context-based emotion-analyzer dedicated for supporting to learn tonality in music courses. This emotion-analyzer realizes a new music retrieval environment to find and visualize music items with considering genre dependent perceptual preference of music. This system generates emotive annotations for music by analyzing tonality along with a timeline. The system helps users to identify music tonality from the viewpoint of emotions. Tonality is a musical system that is constructed by sound elements, such as harmonies and melodies. Change of tonality causes change of impression. This system realizes an automatic time-duration selector that detects repetitions and bridges by analyzing physical and structural music features, such as pitch and tonality. This system enables users to submit emotive keywords as a query for retrieving music according to the impressive changes in each musical piece. This paper shows a prototype system that searches MIDI music files by analyzing them automatically. This paper also shows several experimental results for clarifying the feasibility of the system.
AB - This paper presents a context-based emotion-analyzer dedicated for supporting to learn tonality in music courses. This emotion-analyzer realizes a new music retrieval environment to find and visualize music items with considering genre dependent perceptual preference of music. This system generates emotive annotations for music by analyzing tonality along with a timeline. The system helps users to identify music tonality from the viewpoint of emotions. Tonality is a musical system that is constructed by sound elements, such as harmonies and melodies. Change of tonality causes change of impression. This system realizes an automatic time-duration selector that detects repetitions and bridges by analyzing physical and structural music features, such as pitch and tonality. This system enables users to submit emotive keywords as a query for retrieving music according to the impressive changes in each musical piece. This paper shows a prototype system that searches MIDI music files by analyzing them automatically. This paper also shows several experimental results for clarifying the feasibility of the system.
KW - E-learning
KW - Multimedia information systems
KW - Music course-ware
KW - Technology for education
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=84862288716&partnerID=8YFLogxK
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U2 - 10.2316/P.2011.754-041
DO - 10.2316/P.2011.754-041
M3 - Conference contribution
AN - SCOPUS:84862288716
SN - 9780889868908
T3 - Proceedings of the IASTED International Conference on Technology for Education, TE 2011
SP - 37
EP - 45
BT - Proceedings of the IASTED International Conference on Technology for Education, TE 2011
T2 - IASTED International Conference on Technology for Education, TE 2011
Y2 - 14 December 2011 through 16 December 2011
ER -