Subject: Re: recognizing a source by its harmonic structure From: "F.R.Maintenant" <F.R.Maintenant(at)OPEN.AC.UK> Date: Fri, 27 Jun 2003 18:48:37 +0100It should be mentioned that most of these articles can be find on the net. see: Audio Research Group, Tampere University Of Technology, Finland – http://www.c <http://www.cs.tut.fi/sgn/arg/> s.tut.fi/sgn/arg/BM__Hlt24948962 Antti Eronen – Automatic musical instrument recognition, pattern and speech recognition http://www.cs. <http://www.cs.tut.fi/~eronen/> tut.fi/~eronen/ Departement TSI : [Traitement du Signal et des images / Signal and Imaes Processing], Ecole Nationale Superieure des Telecommunications, Telecom Paris, France – <http://www.tsi.enst.fr/tsi/dep-tsi-eng.html> http://www.tsi.enst.fr/tsi/dep-tsi-eng.html Yves Grenier – Separation of musical sounds <http://www.tsi.enst.fr/~grenier/> http://www.tsi.enst.fr/~grenier/ EMS : [Experimental Music Studios], University of Illinois, USA – http://ems.music.ui <http://ems.music.uiuc.edu/> uc.edu/BM__Hlt24955182 James Beauchamp – Spectral Dynamic Synthesis, spectral centroid variation, spectral envelope irregularity http://ems.music.uiuc.e <http://ems.music.uiuc.edu/~beaucham/> du/~beaucham/ MIT Media Lab, MIT, Cambridge, MA, USA – http://www. <http://www.media.mit.edu/> media.mit.edu/BM__Hlt24959265BM__Hlt24959276 1. Hyperinstruments, MIT, USA - http://www. <http://www.media.mit.edu/hyperins/> media.mit.edu/hyperins/BM__Hlt24959284 Tod Machover – Computer Music, Intelligent Music Instruments http://web <http://web.media.mit.edu/~tod/> .media.mit.edu/~tod/BM__Hlt24959318BM__Hlt24959327 Eric Métois – Media Sound Information http://xenia.media <http://xenia.media.mit.edu/~metois/Phd/eymphd.pdf> .mit.edu/~metois/Phd/eymphd.pdfBM__Hlt24959379BM__Hlt24959360 http://xenia <http://xenia.media.mit.edu/~metois/> .media.mit.edu/~metois/BM__Hlt24959422 2. Music, Mind and Machine Group, MIT, USA -http://sound.m <http://sound.media.mit.edu/index.html> edia.mit.edu/index.htmlBM__Hlt24959521BM__Hlt18381860 Judith C. Brown – Audio Signal Processing http://www.wellesl <http://www.wellesley.edu/Physics/brown/jbrown.html> ey.edu/Physics/brown/jbrown.htmlBM__Hlt24959554 Barry Vercoe – Synthetic Listeners and Performers http://web.m <http://web.media.mit.edu/~bv/> edia.mit.edu/~bv/BM__Hlt24962851 Keith D. Martin - Sound-Source <http://xenia.media.mit.edu/~kdm/research> Recognition: A Theory and Computational Model http://xenia.media.mit.edu/~ <http://xenia.media.mit.edu/~kdm/research/> kdm/research/BM__Hlt24962904 Eric Scheirer – MPEG-4, music-analysis systems, Synthetic listeners, structured audio http://web.media.mit.edu/~eds/ <http://web.media.mit.edu/~eds/> (inc. thesis : Music-Listening Systems) MMK : [Mensh-Maschine-Kommunikation], Technische Universität München, Germany - http://www.mm <http://www.mmk.e-technik.tu-muenchen.de/index_e.html> k.e-technik.tu-muenchen.de/index_e.htmlBM__Hlt24962935 Ernst Terhardt – Perception of Auditory Pitch http://www.mmk <http://www.mmk.e-technik.tu-muenchen.de/persons/ter.html> .e-technik.tu-muenchen.de/persons/ter.html MTG : [ Music Technology Group], Pompeu Fabra University, Barcelona, Spain -http://w <http://www.iua.upf.es/mtg/eng/> ww.iua.upf.es/mtg/eng/BM__Hlt18397275BM__Hlt24963139BM__Hlt24963399 Xavier Serra – Spectral processing http://www.iua.up <http://www.iua.upf.es/~xserra/angles.html> f.es/~xserra/angles.htmlBM__Hlt24963305BM__Hlt24963265BM__Hlt24963223BM__Hlt 24963207 Perfecto Herrera – Transmitting Audio Content as Sound Object <http://www.iua.upf.es/~perfe/> http://www.iua.upf.es/~perfe/ Parmly Hearing Institute, Loyola University Chicago, USA – http://www.parml <http://www.parmly.luc.edu/> y.luc.edu/BM__Hlt24965309 Gregory Sandell – Sharc database (http://www. <http://www.auditory.org/postings/1994/206.html> auditory.org/postings/1994/206.htmlBM__Hlt24965329BM__Hlt24965321 ; http://sparky.ls.luc.edu/sandell/sharc/ <http://sparky.ls.luc.edu/sandell/sharc/README.html> README.htmlBM__Hlt18823078 , http://spark <http://sparky.ls.luc.edu/sharc/> y.ls.luc.edu/sharc/BM__Hlt24965353) http://www.tedcrane.com/DanceDB/DisplayIdent.com?key=GREG_SANDELL <http://www.tedcrane.com/DanceDB/DisplayIdent.com?key=GREG_SANDELL> Peabody Institute, Baltimore, USA - http://www.pe <http://www.peabody.jhu.edu/> abody.jhu.edu/BM__Hlt24965546 Ichiro Fujinaga – Optical music recognition, lazy learning (exemplar-based learning), digital signal processing, pattern recognition, music perception. http://gigue.peabody.j <http://gigue.peabody.jhu.edu/~ich/> hu.edu/~ich/BM__Hlt24965556BM__Hlt25480710BM__Hlt29891118BM__Hlt29884728BM__ Hlt24963004BM__Hlt24962989 BM__Hlt24955207 BM__Hlt24948985-----Original Message----- From: Ladislava Janku [mailto:jankul(at)LAB.FELK.CVUT.CZ] Sent: Fri 27/06/2003 09:28 To: AUDITORY(at)LISTS.MCGILL.CA Cc: Subject: Re: recognizing a source by its harmonic structure Hi! There is lot of work done in music instruments classification by frequency spectrum, cepstrum or other approaches For example, the following papers concern this problem: Brown, J.C. (1999). ``Computer identification of musical instruments using pattern recognition with cepstral coefficients as features'' J. Acoust. Soc. Am. 105, 1933-1941. Herrera P., Amatriain X., Batlle E., and Serra X. Towards Instrument Segmentation for Music Content Description: a Critical Review of Instrument Classification Techniques. In Proc. of International Symposium on Music Information Retrieval, 2000. Liu, Wan Feature selection for automatic classification of musical instrument sounds Proceedings of the first ACM/IEEE-CS joint conference on Digital libraries Roanoke, Virginia, United States Pages: Pages: 247 - 248 Year of Publication: 2001 ISBN:1-58113-345-6 Brown, J.C. (1996). "Frequency ratios of spectral components of musical sounds" J. Acoust. Soc. Am. 99, 1210-1218. Brown, J.C., Houix, O. & McAdams, S. (2001) Feature dependence in the automatic identification of musical woodwind instruments. J. Acoust. Soc. Am. 109, pp. 1064-1072. Kinoshita, T., Sakai, S. & Tanaka, H. (1999) Musical soundsource identification based on frequency component adaptation. Proc. IJCAI-99 Workshop on ComputationalAuditory Scene Analysis, Stockholm, Sweden. Marques, J. & Moreno, P. (1999) A study of musical instrument classification using Gaussian mixture models andsupport vector machines. Cambridge Research LaboratoryTechnical Report Series CRL/4. Martin, K. (1999) Sound-source recognition: A theory andcomputational model. PhD Thesis, MIT G.J. Brown, J. Egging A MISSING FEATURE APPROACH TO INSTRUMENT IDENTIFICATION IN POLYPHONIC MUSIC, ICASSP03 Ladislava Janku ----- Original Message ----- From: "Gregoire, Jerry" <jgregoire(at)ECE.MONTANA.EDU> To: <AUDITORY(at)LISTS.MCGILL.CA> Sent: Thursday, June 26, 2003 10:33 PM Subject: recognizing a source by its harmonic structure > Does anyone know of work done that categorizes sources by patterns in their > harmonic structure. > > An example would be to separate a guitar from a flute using the harmonic > relationships of f0, f1, f2, ... of a guitar compared to the flute's > harmonics. > > Jerry Gregoire >