Using Psycho-Acoustic Models and Self-Organizing Maps to Create ...
Using Psycho-Acoustic Models and Self-Organizing Maps to Create ...
Using Psycho-Acoustic Models and Self-Organizing Maps to Create ...
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
€<br />
€<br />
K<br />
€<br />
K<br />
K<br />
K<br />
€<br />
K<br />
K<br />
€<br />
K<br />
K<br />
K<br />
K<br />
€<br />
K<br />
K<br />
K<br />
€<br />
K<br />
K<br />
€<br />
K<br />
K<br />
K<br />
K<br />
K<br />
€<br />
K<br />
K<br />
K<br />
€<br />
€<br />
€<br />
K<br />
€<br />
€<br />
K<br />
€<br />
<strong>Using</strong> <strong>Psycho</strong>-<strong>Acoustic</strong> <strong>Models</strong> <strong>and</strong> ¢¡¤£¦¥ <strong>to</strong> create a Hierarchical Structuring of Music<br />
[7] M. Dittenbach, A. Rauber, <strong>and</strong> D. Merkl. Recent advances<br />
with the growing hierarchical self-organizing map. In ‚ \ <br />
\ »hs:wBg¤`._$©r$ea \ oRg¢t$Agojbvw' , Advances in<br />
»rƒ~yh¢_‘Lq<br />
<strong>Self</strong>-<strong>Organizing</strong> <strong>Maps</strong>, pages 140–145, Lincoln, Engl<strong>and</strong>, June<br />
13-15 2001. Springer.<br />
[8] B. Feiten <strong>and</strong> S. Günzel. Au<strong>to</strong>matic indexing of a sound<br />
database using self-organizing neural nets. ¨0 ¬ w [ ~7_ \ b [ e<br />
[Q\ g=© , 18(3):53–65, 1994.<br />
[9] J. Foote. An overview of audio information retrieval. b [ © ~e<br />
¬ _Ciz`¢}~7_ ¬ , 7(1):2–10, 1999.<br />
[10] A. Ghias, J. Logan, D. Chamberlin, <strong>and</strong> S. B.C. Query by<br />
humming: Musical information retrieval in an audio database.<br />
In ‚ \ {»rØ~yh¢_u¢¨Fb<br />
236, San Francisco, CA, November 5 - 9 1995. ACM.<br />
[11] S. Kaski. Fast winner search for SOM-based moni<strong>to</strong>ring <strong>and</strong><br />
g¢~©w©=¨0grgƒb [ © ~ ¬ _Ci , pages 231–<br />
retrieval of high-dimensional data. ‚ \ ^Lr{~yh¢_<br />
In<br />
\ ~ HØ$© _ [Q\ © _:~nN \ Ë<br />
g’u<br />
945. IEE, September, 7.-10. 1999.<br />
Ÿu<br />
€Š€<br />
gs~©w©O¨0gr<br />
‰P‰ ¯<br />
, pages 940–<br />
[12] T. Kohonen. <strong>Self</strong>-organized formation of <strong>to</strong>pologically correct<br />
feature maps. dˆ©o©¨ }k:_ \ g._:~$ , 43:59–69, 1982.<br />
[13] T. Kohonen. `._$©r$e7 \ oRg¢t$Ago ¬ :w' . Springer-Verlag, Berlin,<br />
1995.<br />
[14] T. Kohonen. <strong>Self</strong>-organization of very large document collections:<br />
State of the art. ‚ \ {»rØ~yhs_ g¢~©w©.¨0grˆgu \ ~ HØ$©<br />
In<br />
[Q\ © _:~nN \ , pages 65–74, Skövde, Sweden, 1998.<br />
_<br />
[15] T. Kohonen, S. Kaski, K. Lagus, J. Salojärvi, J. Honkela,<br />
V. Paatero, <strong>and</strong> A. Saarela. <strong>Self</strong>-organization of a massive document<br />
collection.<br />
]0]N] «s\ g¢:R$~g¢ˆg<br />
11(3):574–585, May 2000.<br />
K<br />
[16] N. Kosugi, Y. Nishihara, T. Sakata, M. Yamamuro, <strong>and</strong><br />
K. Kushima. A practical query-by-humming system for a large<br />
_ [Q\ ©<br />
_:~nN \ ,<br />
music database. ‚ \ »r¤~yh¢_“u¢¨Fb g¢~©w©0¨0gr…gqb [ © ~e<br />
¬<br />
In<br />
, pages 333–342, Marina del Ray, CA, 2000. ACM.<br />
_Ci<br />
[23] E. Pampalk ©g=iv»rqb [ S$—’uJg=© }Aµ¦a \ oRgst~gsµ<br />
K [ © 9~g¤Lrxb [ vu \ hQA´_: . Master’s thesis, Vienna<br />
University of Technology,<br />
g'i’s5y<br />
2001.<br />
[24] E. Pampalk, A. Rauber, <strong>and</strong> D. Merkl. Content-based organization<br />
<strong>and</strong> visualization of music archives. In ‚ \ Z»rvu¢¨Fb<br />
[ © ~ ¬ _i‹*Œ$Œ©‹ , Juan-les-Pins, France, December 1-6 2002.<br />
b<br />
ACM.<br />
[25] E. Pampalk, A. Rauber, <strong>and</strong> D. Merkl. <strong>Using</strong> smoothed data<br />
his<strong>to</strong>grams for cluster visualization in self-organizing maps.<br />
‚ uLr^~yh¢_ g¢~©w©¨0grƒg _ ["\ © _:~nN \ º<br />
€€<br />
Ÿu<br />
In<br />
\<br />
, Madrid, Spain, August 27-30 2002. Springer.<br />
‹*Œ$Œ©‹ ¯<br />
[26] A. Rauber <strong>and</strong> M. Frühwirth. Au<strong>to</strong>matically analyzing <strong>and</strong><br />
organizing music ‚ \ ¦LrZ~yh¢_ ]·[Q\ ws_g ¨0gr<br />
archives. In<br />
\ h g=i1uJi´g=_Ci « _ChQg'©o}ºr \ Æx<strong>to</strong>y~*©Ø¹ e<br />
gBˆ_:$_<br />
\ \ *_:x ] ¨FÆ|¹i‹*ŒPŒª ¯<br />
, Darmstadt, Germany, Sept. 4-8 2001.<br />
k<br />
Springer.<br />
[27] B. Ripley. ‚~~7_ \ g ˆ_ogsA~g g'i<br />
Cambridge University Press, Cambridge, UK, 1996.<br />
_ ["\ ©<br />
_:~nN \ .<br />
[28] J. Roll<strong>and</strong>, G. Raskinis, <strong>and</strong> J. Ganascia. Musical contentbased<br />
retrieval: An overview of the Melodiscov approach <strong>and</strong><br />
system. In ‚ \ j»rz~yh¢_"u¢¨Fb<br />
pages 81–84, Orl<strong>and</strong>o, FL, 1999. ACM.<br />
gs~©w©|¨0grºg®b [ © ~ ¬ _Ci ,<br />
[29] D. Roussinov <strong>and</strong> H. Chen. Information navigation on the web<br />
by clustering <strong>and</strong> summarizing query results. K gr$ \:¬ ~g<br />
‚ \ _:ygQojg'iƒbvg=o_ ¬ _:g¢~ , 37:789 – 816, 2001.<br />
[30] E. Scheirer. b [ eA¹ y~7_:gsAgQo^`s}~7_ ¬ . PhD thesis, MIT Media<br />
Labora<strong>to</strong>ry, 2000.<br />
[31] M. Schröder, B. Atal, <strong>and</strong> J. Hall. Optimizing digital speech<br />
coders by exploiting masking properties of the human ear.<br />
[Q\ g=©Ø»r ~yh¢_Žû [ ~©N`=$_:~}Ë»rmu ¬ _ \ , 66:1647–<br />
1652, 1979.<br />
[17] C. Liu <strong>and</strong> P. Tsai. Content-based retrieval of mp3 music<br />
objects. ‚ \ úLrË~yh¢_ g¢~©w©¢¨0grfg<br />
In<br />
¬ _:gs~|:¨<br />
…g=nˆ©t_io_xbvg'o_<br />
Atlanta, Georgia, 2001. ACM.<br />
gr \:¬ ~g g=i<br />
¤b”‹aŒ$Œª ¯<br />
, pages 506 – 511,<br />
[18] M. Liu <strong>and</strong> C. Wan. A study of content-based classification <strong>and</strong><br />
retrieval of audio database. ‚ \ J»r0~yh¢_ gs~©w©Æ¢~*k_ ] g'e<br />
In<br />
\ AgQoËg'i•uØwRw=© ~g¢^`¢} ¬ w" [Q¬ Æ ] u{`–‹*Œ$Œª ¯<br />
,<br />
oAg.__<br />
Grenoble, France, 2001. IEEE.<br />
[19] D. Merkl <strong>and</strong> A. Rauber. Document classification with unsupervised<br />
neural networks. In F. Crestani <strong>and</strong> G. Pasi, edi<strong>to</strong>rs,<br />
Physica Verlag, 2000.<br />
`=»r~N¨0 ¬ w [ ~AgQoxAg<br />
gr \¬ ~g J_:~ \ *_:´© , pages 102–121.<br />
[20] K. Oh, Y. Feng, K. Kaneko, A. Makinouchi, <strong>and</strong> S. Bae. SOMbased<br />
R*-tree for similarity retrieval. ‚ \ c»rj~yh¢_ g¢~©w©<br />
In<br />
¬ {r$ \ uJi´g'_izu·wRw'© ~gs ,<br />
¨0grºg¤Æ¢~*k_u`s}~7_<br />
pages 182–189, Hong-Kong, China, April 18-21 2001. IEEE.<br />
[21] K. Oh, K. Kaneko, <strong>and</strong> A. Makinouchi. Image classification<br />
<strong>and</strong> retrieval based on wavelet-som. In K gs~©w©=`¢} ¬ w" [Q¬<br />
u·ww=© ~gs Ag g¢e «"\ Riy~g=© ] g¢´ \ g'e<br />
¬<br />
gcÆ¢~*Rk$_ € «4] w ‰$‰ ¯<br />
, pages 164–167, Kyo<strong>to</strong>, Japan, November<br />
28-30 1999.<br />
_:gs~xÆu<br />
IEEE.<br />
[22] F. Pachet <strong>and</strong> D. Cazaly. A taxonomy of musical genres. In<br />
‚ \ ¤»r~yh¢_<br />
[ © ~ ¬ _Ci<br />
gs~©w©4¨0grJg˨0g¢~7_:gs~ed|_Ci¢b<br />
¯<br />
, Paris, France, 2000.<br />
u¢aC‹*Œ$Œ$Œ<br />
g'e<br />
[32] O. Simula, P. Vasara, J. Vesan<strong>to</strong>, <strong>and</strong> R. Helminen. The selforganizing<br />
map in industry analysis. In L. Jain <strong>and</strong> V. Vemuri,<br />
edi<strong>to</strong>rs, g=i [ ~ \ ©auØwRw=© ~g¢ˆLr<br />
Washing<strong>to</strong>n, DC., 1999. CRC Press.<br />
K<br />
_ [Q\ ©<br />
_:~nN \ ,<br />
[33] G. Tzanetakis, G. Essl, <strong>and</strong> P. Cook. Au<strong>to</strong>matic musical genre<br />
classification of audio signals. ‚ \ In<br />
[ gr \:¬ ~gvˆ_:~ \ *_:´©Ø `"b<br />
b<br />
¬ w" [Q¬ g gs~©w©5`s}<br />
¯<br />
, Blooming<strong>to</strong>n, In-<br />
<br />
diana, Oc<strong>to</strong>ber 15-17 2001.<br />
[34] A. Ultsch <strong>and</strong> H. Siemon. Kohonen’s self-organizing feature<br />
maps for explora<strong>to</strong>ry data analysis. In ‚ \ …»r|~yh¢_<br />
Netherl<strong>and</strong>s, 1990. Kluwer.<br />
\ ©<br />
_:~nN \ ú¨0grº<br />
Kt€Š€<br />
gs~©w©<br />
_ [ e<br />
¨vw ‰dŒ ¯<br />
, pages 305–308, Dordrecht,<br />
[35] E. Wold, T. Blum, D. Keislar, <strong>and</strong> J. Whea<strong>to</strong>n. Content-based<br />
classification search <strong>and</strong> retrieval of audio. K ]0]N] b [ © ~ ¬ _$e<br />
i , 3(3):27–36, Fall 1996.<br />
[36] H. Zhang <strong>and</strong> D. Zhong. A scheme for visual feature based<br />
image indexing. ‚ \ ¢LrJ~yh¢_ `˜ « Å¢`"‚<br />
K ] ¨0gr{gq`s~* \ e<br />
In<br />
\ *_:´©9r$ \ K ¬ o_¤g'i1s5i_C…Æ¢~*k_: , pages<br />
o_xg'i…J_:~<br />
36–46, San Jose, CA, February 4-10 1995.<br />
[37] E. Zwicker <strong>and</strong> H. ‚·}hsR [ ~$µNX5R$~xg=i bvie<br />
Fastl.<br />
, volume 22 of `._ \ *_:J»r gr \¬ ~gZ`=$*_:g'_: . Springer,<br />
_$©<br />
Berlin, 2. edition, 1999.<br />
r \¬ ~g uJ_: