O'Reilly logo

Music Emotion Recognition by Homer H. Chen, Yi-Hsuan Yang

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Saunder January 24, 2011 10:39 book
References
[1] All music guide. [Online] http://www.allmusic.com/.
[2] Cool edit pro. [Online] http://www.adobe.com/products/audition/.
[3] GOASEMA – semantic description of musical audio. [Online] http://www.ipem. ugent.be.
[4] Goldwave: Audio editor, recorder, converter, restoration, & analysis software. [Online]
http://www.goldwave.com/.
[5] Gracenote. [Online] http://www.gracenote.com/.
[6] Last.fm. [Online] http://www.last.fm/.
[7] Lingpipe. [Online] http://alias-i.com/lingpipe/.
[8] Lyricwiki. [Online] http://lyrics.wikia.com/.
[9] MATLAB
optimization toolbox. [Online] http://www.mathworks.com/products/
optimization/.
[10] MATLAB wavelet toolbox. [Online] http://www.mathworks.com/products/ wavelet/.
[11] MIREX: Music information retrieval evaluation exchange. [Online] http://www. music-
ir.org/mirex/.
[12] Moodlogic. [Online] http://www.moodlogic.com.
[13] Musicovery: Interactive Web radio. [Online] http://www.musicovery.com/.
[14] Syntonetic. [Online] http://www.syntonetic.com/.
[15] A. Abbasi, H. Chen, S. Thoms, and T. Fu. Affect analysis of Web forums and blogs using
correlation ensembles. IEEE Trans. Knowledge & Data Engineering, 20(9):1168–1180, 2008.
[16] H. F. Abeles and J. W. Chung. Responses to Music, pages 285–342. IMR Press, San Antonio,
TX, 1996.
[17] A. Agresti. Categorical Data Analysis. John Wiley & Sons Publications, Hoboken, New
Jersey, 2002.
[18] A. Aizawa. An information-theoretic perspective of tf-idf measures. Information Processing
and Management, 39:45–65, 2003.
[19] S. O. Ali. Songs and emotions: are lyrics and melodies equal partners. Psychology of Music,
34(4):511–534, 2006.
[20] S. O. Ali and Z. F. Peynircio
ˇ
gu. Songs and emotions: are lyrics and melodies equal partners.
Psychology of Music, 34(4):511–534, 2006.
[21] E. Allamanche, J. Herre, O. Helmuth, B. Fr
¨
oba, T. Kasten, and M. Cremer. Content-based
identification of audio material using MPEG-7 low level description. In Proc. Int. Conf.
Music Information Retrieval, pages 197–204, 2001.
[22] K. Anderson and P. W. McOwan. A real-time automated system for the recognition of
human facial expressions. IEEE Trans. System, Man & Cybernetics, 36(1):96–105, 2006.
[23] S. Arifin and P. Y. K. Cheung. Affective level video segmentation by utilizing the pleasure-
arousal-dominance information. IEEE Trans. Multimedia, 10(7):1325–1341, 2008.
219
Saunder January 24, 2011 10:39 book
220 References
[24] F. R. Bach and M. I. Jordan. Learning spectral clustering, with application to speech sepa-
ration. J. Machine Learning Research, 7:1963–2001, 2006.
[25] S. A. Banawan and N. M. Zeidat. A comparative study of load sharing in heterogeneous
multicomputersystems. In Proc. Annual Simulation Symposium, pages 22–31, 1992.
[26] L. Barrington, D. O’Malley, D. Turnbull, and G. Lanckriet. Herd the music—a social music
annotation game. In Proc. Int. Conf. Music Information Retrieval, 2008.
[27] M. Bartoszewski, H. Kwasnicka, U. Markowska-Kaczmar, and P. B. Myszkowski. Extraction
of emotional content from music data. In Proc. Computer Information Systems and Industrial
Management Applications, pages 293–299, 2008.
[28] D. Beard and K. Gloag. Musicology: the Key Concepts. Routledge, New York, 2005.
[29] J. P. Bello, L. Daudet, S. Abdallah, C. Duxbury, M. Davies, and M. B. Sandler. A tutorial on
onset detection in music signals. IEEE Trans. Speech and Audio Processing, 13(5):1035–1047,
2005.
[30] J. P. Bello and J. Pickens. A robust mid-level representation for harmonic content in music
signals. In Proc. Int. Conf. Music Information Retrieval, pages 304–311, 2005.
[31] E. Benetos, M. Kotti, and C. Kotropoulos. Large scale musical instrument identifi-
cation. In Proc. Int. Conf. Music Information Retrieval, 2007. [Online] http://www.
ifs.tuwien.ac.at/mir/muscle/del/audio
tools.html#Sound DescrToolbox.
[32] L. Bergroth, H. Hakonen, and T. Raita. A survey of longest common subsequence algo-
rithms. In Proc. Int. Symp. String Processing Information Retrieval, pages 322–336, 2000.
[33] E. Bigand, S. Vieillard, F. Madurell, J. Marozeau, and A. Dacquet. Multidimensional scaling
of emotional responses to music: The effect of musical expertise and of the duration of the
excerpts. Cognition and Emotion, 19(8):1113–1139, 2005.
[34] K. Bischoff, C. S. Firan, R. Paiu, W. Nejdl, C. Laurier, and M. Sordo. Music mood and
theme classification - a hybrid approach. In Proc. Int. Conf. Music Information Retrieval,
pages 657–662, 2009.
[35] L. Bo and C. Sminchisescu. Twin Gaussian processes for structured prediction. Int. J.
Computer Vision, 87(1–2):28–52, 2010.
[36] E. V. Bonilla, K. M. A. Chai, and C. K. I. Williams. Multi-task Gaussian process prediction.
In Proc. Conf. Neural Information Processing Systems, pages 164–170, 2008.
[37] A. Bosch, A. Zisserman, and X. M. noz. Scene classification using a hybrid generative
discriminative approach. IEEE Trans. Pattern Analysis & Machine Intelligence, 30(4):712–
727, 2008.
[38] Z. I. Botev, J. F. Grotowski, and D. P. Kroese. Kernel density estimation via diffusion.
Annals of Statistics, 2009. Submitted.
[39] A. W. Bowman and A. Azzalini. Applied Smoothing Techniques for Data Analysis. Oxford
University Press, New York, 1997.
[40] S. P. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, Cam-
bridge, UK, 2004.
[41] P. Boyle and M. Frean. Dependent Gaussian processes. In Proc. Conf. Neural Information
Processing Systems, pages 217–224, 2004.
[42] C. J. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton, and G. Hullender.
Learning to rank using gradient descent. In Proc. IEEE Int. Conf. Machine Learning, pages
89–96, 2005.
[43] R. Burkard. Sound pressure level measurement and spectral analysis of brief acoustic tran-
sients. Electroencephalography and Clinical Neurophysiology, 57(1):83–91, 1984.
[44] D. Cabrera. Psysound: A computer program for psycho-acoustical analysis. In Proc. Aus-
tralian Acoustic Society Conf., pages 47–54, 1999. [Online] http://psysound. wikidot.com/.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required