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Music Technology Group
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#	Item
1	EXPLORING CUSTOMER REVIEWS FOR MUSIC GENRE CLASSIFICATION AND EVOLUTIONARY STUDIES Sergio Oramas1 , Luis Espinosa-Anke2 , Aonghus Lawlor3 , Xavier Serra1 , Horacio Saggion2 1 Music Technology Group, Universitat Pompeu Fa Add to Reading List Source URL: wp.nyu.edu Language: English - Date: 2016-08-16 16:20:27
2	Foafing the Music: Bridging the semantic gap in music recommendation ` Oscar Celma1 Music Technology Group, Universitat Pompeu Fabra, Barcelona, SPAIN Add to Reading List Source URL: iswc2006.semanticweb.org Language: English - Date: 2012-11-15 10:09:29
3	INSYS GROUP CASE STUDY: Telco Hadoop Integration Introduction Telecommunication providers process millions of phone calls per second, as well as provide services for web browsing, videos, television, streaming music and Add to Reading List Source URL: www.insys.com Language: English - Date: 2016-04-19 12:49:39 Computing Free software Software Cloud infrastructure Data management Apache Software Foundation Big data Technology forecasting Transaction processing Apache Hadoop
4	CLAM, an Object Oriented Framework for Audio and Music Pau Arum´ı and Xavier Amatriain Music Technology Group, Universitat Pompeu FabraBarcelona, Spain {parumi,xamat}@iua.upf.es Add to Reading List Source URL: lac.zkm.de Language: English - Date: 2005-06-24 21:08:11 Software Computing Computer programming Application programming interfaces Widget toolkits CLAM Qt Advanced Linux Sound Architecture Widget PortAudio
5	A GENERALIZED BAYESIAN MODEL FOR TRACKING LONG METRICAL CYCLES IN ACOUSTIC MUSIC SIGNALS Ajay Srinivasamurthy ⋆ , Andre Holzapfel † , Ali Taylan Cemgil ‡ , Xavier Serra ⋆ ⋆ Music Technology Group, Universitat Add to Reading List Source URL: www.rhythmos.org Language: English - Date: 2016-02-09 05:50:48 Music Patterns Statistics Entertainment Cognitive musicology Rhythm Tempo Metre Time signature Normal distribution Duration
6	Primary Sources Maurice Carlin United Kingdom This assignment is based on the activities of an informal collective of which I am a member, ‘Studio Group’. Our collective explores new possibilities for how, when, and Add to Reading List Source URL: christinewongyap.com Language: English - Date: 2014-03-02 20:18:10 9 Music industry Draft:Holzner Anton Open Space Technology
7	Speeding Up Tracking by Ignoring Features Lu Zhang Hamdi Dibeklio˘glu Laurens van der Maaten Pattern Recognition & Bioinformatics Group, Delft University of Technology Mekelweg 4, 2628 CD Delft, The Netherlands Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Animal identification Tracking Music tracker Minimum bounding box Conference on Computer Vision and Pattern Recognition Video tracking Tracker Science and technology Computer science Vision
8	LEARNING TEMPORAL FEATURES USING A DEEP NEURAL NETWORK AND ITS APPLICATION TO MUSIC GENRE CLASSIFICATION Il-Young Jeong and Kyogu Lee Music and Audio Research Group Graduate School of Convergence Science and Technology, Add to Reading List Source URL: wp.nyu.edu Language: English - Date: 2016-08-16 16:20:29 Times Celebex California locations by race
9	CROSS-COLLECTION EVALUATION FOR MUSIC CLASSIFICATION TASKS Dmitry Bogdanov, Alastair Porter, Perfecto Herrera, Xavier Serra Music Technology Group, Universitat Pompeu Fabra Add to Reading List Source URL: wp.nyu.edu Language: English - Date: 2016-08-16 16:20:29 Machine learning Support vector machine Cross-validation Statistical classification Classifier Pattern recognition Test set
10	LIFELONG LEARNING INTEREST GROUP EDUCATION FOR PERSONAL Add to Reading List Source URL: lllplatform.eu Language: English - Date: 2016-05-04 07:43:31 Educational psychology Lifelong learning Adult education Learning environment Collaborative learning Educational technology Informal learning Learning Peer learning Music education European Association for the Education of Adults European Lifelong Learning Indicators

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