References
- Bartsch, M. A. , & Wakefield, G. H. (2005). Audio thumbnailing of popular music using chroma-based representations. IEEE Transactions on Multimedia , 7 , 96–104.
- Benadon, F. (2006). Slicing the beat: Jazz eighth-notes as expressive microrhythm. Ethnomusicology , 50 , 73–98.
- Berliner, P. F. (1994). Thinking in Jazz: The infinite art of improvisation . Chicago: University of Chicago Press.
- Böck, S. , Arzt, A. , Krebs, F. , & Schedl, M. (2012). Online real-time onset detection with recurrent neural networks. In Proceedings of the International Conference on Digital Audio Effects (DAFx) , York, UK.
- Busse, W. G. (2002). Toward objective measurement and evaluation of jazz piano performance via MIDI-based groove quantize templates. Music Perception , 19 , 443–461.
- Cannam, C. , Landone, C. , & Sandler, M. B. (2010). Sonic visualiser: An open source application for viewing, analysing, and annotating music audio files. In Proceedings of the International Conference on Multimedia (pp. 1467–1468). Florence, Italy.
- Collier, G. L. , & Collier, J. L. (2002). A study of timing in two louis armstrong solos. Music Perception , 19 , 463–483.
- Davies, M. , Madison, G. , Silva, P. , & Gouyon, F. (2013). The effect of microtiming deviations on the perception of groove in short rhythms. Music Perception , 30 , 497–510.
- Dittmar, C. , & Gärtner, D. (2014). Real-time transcription and separation of drum recordings based on NMF decomposition. In Proceedings of the International Conference on Digital Audio Effects (DAFx) (pp. 187–194). Erlangen, Germany.
- Dittmar, C. , Pfleiderer, M. , & Müller, M. (2015). Automated estimation of ride cymbal swing ratios in jazz recordings. In Proceedings of the International Conference on Music Information Retrieval (ISMIR) (pp. 271–277). Málaga, Spain.
- Dixon, S. (2006). Onset detection revisited. In Proceedings of the International Conference on Digital Audio Effects (DAFx) (pp. 133–137). Montreal, Quebec, Canada.
- Dixon, S. , Gouyon, F. , & Widmer, G. (2004). Towards characterisation of music via rhythmic patterns. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR) (pp. 509–516). Barcelona, Spain.
- Ellis, D. P. (2007). Beat tracking by dynamic programming. Journal of New Music Research , 36 , 51–60.
- Ellis, M. C. (1991). An analysis of ‘swing’ subdivision and asynchronization in three jazz saxophonists. Perceptual and Motor Skills , 73 , 707–713.
- Eppler, A. , Männchen, A. , Abeßer, J. , Weiß, C. , & Frieler, K. (2014). Automatic style classification of jazz records with respect to rhythm, tempo, and tonality. In Proceedings of the Conference on Interdisciplinary Musicology (CIM) , Berlin, Germany.
- Eyben, F. , Böck, S. , Schuller, B. , & Graves, A. (2010). Universal onset detection with bidirectional long short-term memory neural networks. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR) (pp. 589–594). Utrecht, The Netherlands.
- Foote, J. , & Uchihashi, S. (2001). The beat spectrum: A new approach to rhythm analysis. In Proceedings of the International Conference on Multimedia and Expo (ICME) , Los Alamitos, CL, USA.
- Friberg, A. , & Sundström, A. (2002). Swing ratios and ensemble timing in jazz performance: Evidence for a common rhythmic pattern. Music Perception , 19 , 333–349.
- Frieler, K. , Zaddach, W.-G. , Abeßer, J. , & Pfleiderer, M. (2013). Introducing the jazzomat project and the melospy library. In Third International Workshop on Folk Music Analysis , Amsterdam, The Netherlands.
- Grosche, P. , & Müller, M. (2011a). Extracting predominant local pulse information from music recordings. IEEE Transactions on Audio, Speech, and Language Processing , 19 , 1688–1701.
- Grosche, P. , & Müller, M. (2011b). Tempogram toolbox: MATLAB tempo and pulse analysis of music recordings. In Late-Breaking and Demo Session of the International Conference on Music Information Retrieval (ISMIR) . Miami, FL, USA.
- Gruhne, M. , & Dittmar, C. (2009). Improving rhythmic pattern features based on logarithmic preprocessing. In Proceedings of the Audio Engineering Society (AES) Convention , Munich, Germany.
- Holzapfel, A. , & Stylianou, Y. (2009). A scale transform based method for rhythmic similarity of music. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (pp. 317–320). Taipei, Taiwan.
- Holzapfel, A. , & Stylianou, Y. (2011). Scale transform in rhythmic similarity of music. IEEE Transactions on Audio, Speech, and Language Processing , 19 , 176–185.
- Honing, H. , & de Haas, W. B. (2008). Swing once more: Relating timing and tempo in expert jazz drumming. Music Perception: An Interdisciplinary Journal , 25 , 471–476.
- Jensen, J. H. , Christensen, M. G. , & Jensen, S. H. (2009). A tempo-insensitive representation of rhythmic patterns. In Proceedings of the European Signal Processing Conference (EUSIPCO) (pp. 1509–1512). Glasgow, Scotland.
- Jensen, K. (2006). Multiple scale music segmentation using rhythm, timbre, and harmony. EURASIP Journal on Advances in Signal Processing , 2007 , 1–11.
- Kerschbaumer, F. (1978). Miles Davis: Stilkritische Untersuchungen zur musikalischen Entwicklung seines Personalstils . Graz: Studies in jazz research. Akademische Druck und Verlagsanstalt.
- Kurth, F. (2013). The shift-ACF Detecting multiply repeated signal components. In Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) (pp. 1–4). New Paltz, NY, USA.
- Kurth, F. , Gehrmann, T. , & Müller, M. (2006). The cyclic beat spectrum: Tempo-related audio features for time-scale invariant audio identification. In Proceedings of the International Conference on Music Information Retrieval (ISMIR) (pp. 35–40). Victoria, Canada.
- Marchand, U. , & Peeters, G. (2014). The modulation scale spectrum and its application to rhythm-content description. In Proceedings of the International Conference on Digital Audio Effects (DAFx) (pp. 167–172). Erlangen, Germany.
- Marchand, U. , & Peeters, G. (2015). Swing ratio estimation. In Proceedings of the International Conference on Digital Audio Effects (DAFx) (pp. 423–428). Trondheim, Norway.
- Müller, M. (2015). Fundamentals of music processing . Heidelberg: Springer Verlag.
- Parsons, W. , & Cholakis, E. (1995). It don’t mean a thing if it ain’t dang, dang-a dang!. Downbeat , 52 , 61.
- Peeters, G. (2005). Rhythm classification using spectral rhythm patterns. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR) (pp. 644–647). London, UK.
- Pfleiderer, M. (2006). Rhythmus: Psychologische, theoretische und stilanalytische Aspekte populärer Musik . Bielefeld: Transcript.
- Prockup, M. , Ehmann, A. F. , Gouyon, F. , Schmidt, E. M. , & Kim, Y. E. (2015). Modeling musical rhythm at scale with the music genome project. In Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) . New Paltz, NY, USA.
- Reinholdsson, P. (1987). Approaching jazz performances empirically. some reflections on methods and problems. Action and Perception in Rhythm and Music , 55 , 105–125.
- Rioul, O. , & Vetterli, M. (1991). Wavelets and signal processing. IEEE Signal Processing Magazine , 8 , 14–38.
- Röbel, A. , Pons, J. , Liuni, M. , & Lagrange, M. (2015). On automatic drum transcription using non-negative matrix deconvolution and itakura saito divergence. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP (pp. 414–418). Brisbane, Australia.
- Rose, R. F. (1989). An analysis of timing in jazz rhythm section performances, PhD thesis, University of Texas.
- Southall, C. , Stables, R. , & Hockman, J. (2016). Automatic drum transcription using bi-directional recurrent neural networks. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR) (pp. 591–597). New York City, NY.
- Sturm, B. L. (2012). An analysis of the GTZAN music genre dataset. In Proceedings of the International ACM Workshop on Music Information Retrieval with User-Centered and Multimodal Strategies MIRUM (pp. 7–12). Nara, Japan.
- Vogl, R. , Dorfer, M. , & Knees, P. (2017). Drum transcription from polyphonic music with recurrent neural networks. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (pp. 201–205). New Orleans, LA, USA.
- Völkel, T. , Abeßer, J. , Dittmar, C. , & Großmann, H. (2010). Automatic genre classification on latin music using characteristic rhythmic patterns. In Proceedings of the Audio Mostly : A Conference on Interaction with Sound , Piteå, Sweden.
- Wesolowski, B. C. (2012). Testing a model of jazz rhythm: Validating a microstructural swing paradigm, PhD thesis, University of Miami, Miami, FL, USA.
- Wu, C.-W. , & Lerch, A. (2015). Drum transcription using partially fixed non-negative matrix factorization with template adaptation. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR) (pp. 257–263). Málaga, Spain.