Biblio

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Susini, P., Misdariis N., Lemaitre G., Houix O., Rocchesso D., Polotti P., et al. (2006).  Closing the loop of sound evaluation and design. Perceptual Quality of Systems. Abstract
Scholler, S., & Purwins H. (2011).  Sparse Approximations for Drum Sound Classification. IEEE Journal of Selected Topics in Signal Processing. 5(5), 933 - 940. Abstract
video/quicktime iconatomic_function_learning.mov
application/pdf iconScholler_Purwins_IEEE_JSTSP_2011_SparseDrumClass.pdf
application/zip iconsparse_classification_code.zip
Scholler, S., & Purwins H. (2010).  Sparse Coding for Drum Sound Classification and its Use as a Similarity Measure. 3rd International Workshop on Machine Learning and Music (MML’10) at ACM Multimedia 2010 . Abstract
application/pdf iconacm_ml_sparse.pdf
Salselas, I., Hazan A., Herrera P., & Purwins H. (2008).  The Development of Melodic Representations at Early Age: Towards a Computational Model.. Music, Language and the Mind 2008. Abstract
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Purwins, H., Holonowicz P., & Herrera P. (2009).  Polynomial Extrapolation for Prediction of Surprise Based on Loudness - A Preliminary Study . Sound and Music Computing Conference. Abstract
Purwins, H., Blankertz B., & Obermayer K. (2007).  Toroidal Models in Tonal Theory and Pitch-Class Analysis. Computing in Musicology (Tonal Theory for the Digital Age ). 15, 73–98. Abstract
Purwins, H., Blankertz B., Dornhege G., & Obermayer K. (2004).  Scale Degree Profiles from Audio Investigated with Machine Learning. Audio Engineering Society Convention. Abstract
Purwins, H., Graepel T., Blankertz B., & Obermayer K. (2004).  Correspondence analysis for visualizing interplay of pitch class, key, and composer. (Guerino Mazzola, Thomas Noll, Emilio Luis-Puebla, Ed.).Perspectives in Mathematical and Computational Music Theory. 432-454. Abstract
Purwins, H., Blankertz B., & Obermayer K. (2001).  Constant Q Profiles for Tracking Modulations in Audio Data. International Computer Music Conference. 407-410.
Purwins, H., Grachten M., Herrera P., Hazan A., Marxer R., & Serra X. (2008).  Computational Models of Music Perception and Cognition II: Domain-Specific Music Processing. Physics of Life Reviews. 5(3), 169-182. Abstract
Purwins, H., Normann I., & Obermayer K. (2005).  Unendlichkeit - Konstruktion akustischer Paradoxien. (Manfred Stahnke, Ed.).Mikrotöne und mehr – Auf György Ligetis Hamburger Pfaden. 39-80.
Purwins, H., Blankertz B., & Obermayer K. (2000).  Computing auditory perception. Organised Sound. 5(3), 159-171. Abstract
Purwins, H., & Hardoon D. (2009).  Trends and Perspectives in Music Cognition Research and Technology. Connection Science. 21(2-3), 85-88. Abstract
Purwins, H. (2010).  We Perceive Music before we Understand Speech. Physics of Life Reviews. 7(1), 46. Abstract
application/pdf iconPurwins_Perlovsky_review_PRL_EmotionMusicSpeech.pdf
Purwins, H., & Blankertz B. (2005).  CQ-profiles for key finding in audio. Abstract
Purwins, H., Blankertz B., & Obermayer K. (2000).  A new method for tracking modulations in tonal music in audio data format. International Joint Conference on Neural Network (IJCNN'00). 6, 270-275. Abstract
Purwins, H., Herrera P., Grachten M., Hazan A., Marxer R., & Serra X. (2008).  Computational Models of Music Perception and Cognition I: The Perceptual and Cognitive Processing Chain. Physics of Life Reviews. 5(3), 151-168. Abstract
Papiotis, P., & Purwins H. (2010).   A Lyrics-Matching QBH System for Interactive Environments. Sound and Music Computing Conference. Abstract
application/pdf iconPapiotis_Purwins_QBH_SMC2010.pdf
Papiotis, P., & Purwins H. (2010).  Real-time Accompaniment using lyrics-matching QBH. 7th International Symposium on Computer Music Modeling and Retrieval (CMMR). 279-280. Abstract
application/pdf iconPapiotis_CMMR2010_QBHDemo.pdf
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Normann, I., Purwins H., & Obermayer K. (2001).  Spectrum of Pitch Differences Models the Perception of Octave Ambiguous Tones. International Computer Music Conference. 274-276. Abstract
Normann, I., Purwins H., & Obermayer K. (2001).  Oktavambiguität als Konkurrenz zwischen Tonhöhe und Klangfarbe. DAGA. Abstract
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Marxer, R., Holonowicz P., Hazan A., & Purwins H. (2008).  Dynamical Hierarchical Self-Organization Of Harmonic And Motivic Musical Categories. Acoustics. Abstract
Marxer, R., & Purwins H. (2010).  Unsupervised Incremental Learning and Prediction of Audio Signals. International Symposium on Music Acoustics. Abstract
application/pdf iconMarxerPurwinsUnsupervisedIncrementalPredictionAudioISMA2010.pdf
Marxer, R., Holonowicz P., Purwins H., & Hazan A. (2007).  Dynamical Hierarchical Self-Organization of Harmonic, Motivic, and Pitch Categories . Music, Brain and Cognition. Part 2: Models of Sound and Cognition, held at NIPS). Abstract
Marxer, R., & Purwins H. (2008).  An F-Measure for Evaluation of Unsupervised Clustering with Non-Determined Number of Clusters. Abstract
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