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2016

[1]
S Abdallah, E Benetos, N Gold, S Hargreaves, T Weyde, and D Wolff. Digital music lab: A framework for analysing big music data. In 24th European Signal Processing Conference, pages 1118--1122. Budapest, Hungary, EURASIP, Aug 2016. [ bib ]
[2]
K Agres, J Forth, and GA Wiggins. Evaluation of musical creativity and musical metacreation systems. Computers in Entertainment, 14, Dec 2016. [ bib | DOI ]
[3]
K Agres, D HERREMANS, L Bigo, and D Conklin. The effect of repetitive structure on enjoyment in uplifting trance music. In 14th International Conference for Music Perception and Cognition (ICMPC), pages 280--282, Jun 2016. [ bib ]
[4]
KR Agres, S McGregor, K Rataj, M Purver, and GA Wiggins. Modeling metaphor perception with distributional semantics vector space models. In CEUR Workshop Proceedings, volume 1767, Jan 2016. [ bib ]
[5]
A Allik, G Fazekas, and M Sandler. Ontological representation of audio features. In SEMANTIC WEB - ISWC 2016, PT II, volume 9982, pages 3--11, 2016. [ bib | DOI | http ]
[6]
PA Alvarado Duran and DF STOWELL. Gaussian processes for music audio modelling and content analysis. In IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2016. [ bib ]
[7]
N Barascud, MT Pearce, TD Griffiths, KJ Friston, and M Chait. Brain responses in humans reveal ideal observer-like sensitivity to complex acoustic patterns. Proc Natl Acad Sci U S A, 113:E616--E625, Feb 2016. [ bib | DOI | http ]
[8]
M BARTHET, F Thalmann, G Fazekas, M Sandler, and G Wiggins. Crossroads: Interactive music systems transforming performance, production and listening. In ACM Conference on Human Factors in Computing Systems (CHI), Workshop on Music and HCI, May 2016. [ bib ]
[9]
E Benetos, G Lafay, M Lagrange, and MD Plumbley. Detection of overlapping acoustic events using a temporally-constrained probabilistic model. In IEEE International Conference on Acoustics, Speech, and Signal Processing, pages 6450--6454, Emmanouil Benetos, Queen Mary University of London, School of Electronic Engineering and Computer Science, Mile End Road, London, E1 4NS, United Kingdom, Mar 2016. Shanghai, China, IEEE. [ bib | DOI | .html ]
[10]
E BENETOS and R Schramm. Automatic transcription of vocal quartets. In DMRN+11: Digital Music Research Network Workshop Proceedings 2016. Centre for Digital Music, Queen Mary University of London, Centre for Digital Music, Queen Mary University of London, Dec 2016. [ bib | http ]
[11]
T Cheng, M Mauch, E Benetos, and S Dixon. An attack/decay model for piano transcription. In 17th International Society for Music Information Retrieval Conference, pages 584--590. New York, USA, ISMIR, Aug 2016. [ bib | http ]
[12]
E Chew. Playing with the edge: Tipping points and the role of tonality. MUSIC PERCEPTION, 33:344--366, Feb 2016. [ bib | DOI | http ]
[13]
K CHOI, M sandler, and G fazekas. Text-based lstm networks for automatic music composition. In Conference on Computer Simulation of Musical Creativity, Keunwoo Choi, Queen Mary University of London, EECS, Peter Landin Building, CS.319, London, E1 4FZ, United Kingdom, Jun 2016. Huddersfield, UK. [ bib ]
[14]
ET CHOURDAKIS and JD REISS. Automatic control of a digital reverberation effect using hybrid models. In 60th International Conference: DREAMS (Dereverberation and Reverberation of Audio, Music, and Speech). Leuven, Belgium, Jan 2016. [ bib ]
[15]
BM DE MAN, N Jillings, D Moffat, JD Reiss, and R Stables. Subjective comparison of music production practices using the web audio evaluation tool. In http://c4dm.eecs.qmul.ac.uk/events/wimp2/. Queen Mary University of London, London, UK, Sep 2016. [ bib ]
[16]
BM DE MAN and JD Reiss. The open multitrack testbed: Features, content and use cases. In http://c4dm.eecs.qmul.ac.uk/events/wimp2/. Queen Mary University of London, London, UK, Sep 2016. [ bib ]
[17]
RT Dean and MT Pearce. Algorithmically-generated corpora that use serial compositional principles can contribute to the modeling of sequential pitch structure in non-tonal music. Empirical Musicology Review, 11:27--27, Jul 2016. [ bib | DOI ]
[18]
J Driedger, S Balke, S Ewert, and M Müller. Template-based vibrato analysis in music signals. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR), pages 239--245, New York, USA, 2016. [ bib ]
[19]
S Ewert. Representation of musical structure for a computationally feasible integration with audio-based methods. Dagstuhl Reports (Computational Music Structure Analysis (Dagstuhl Seminar 16092)), 6(2):175--176, Oct 2016. urn: urn:nbn:de:0030-drops-61415. [ bib | DOI | http ]
[20]
S Ewert and M Sandler. Piano transcription in the studio using an extensible alternating directions framework. IEEE/ACM Transactions on Audio Speech and Language Processing, 24:1983--1997, Nov 2016. [ bib | DOI ]
[21]
S Ewert, S Wang, M Müller, and M Sandler. Score-informed identification of missing and extra notes in piano recordings. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR), pages 30--36, New York, USA, 2016. [ bib ]
[22]
J FORTH, K AGRES, MRJ PURVER, and GA WIGGINS. Entraining idyot: timing in the information dynamics of thinking. Frontiers in Psychology, 7:1575--1575, Oct 2016. [ bib | DOI | http ]
[23]
B Gingras, MT Pearce, M Goodchild, RT Dean, G Wiggins, and S McAdams. Linking melodic expectation to expressive performance timing and perceived musical tension. Journal of experimental psychology. Human perception and performance, 42:594--609, Apr 2016. [ bib | DOI ]
[24]
NC Hansen, M Sadakata, and M Pearce. Nonlinear changes in the rhythm of european art music: Quantitative support for historical musicology. Music Perception: An Interdisciplinary Journal, 33:414--431, Apr 2016. [ bib | DOI ]
[25]
NC Hansen, P Vuust, and M Pearce. "if you have to ask, you'll never know": Effects of specialised stylistic expertise on predictive processing of music. PLOS ONE, 11:e0163584--e0163584, Oct 2016. [ bib | DOI ]
[26]
K Hayes, M BARTHET, Y Wu, L Zhang, and N Bryan-Kinns. A participatory live music performance with the open symphony system. In ACM Conference on Human Factors in Computing Systems (CHI): Interactivity, May 2016. [ bib | DOI ]
[27]
PGT HEALEY, C HOWES, J HOUGH, and MRJ PURVER. Better late than now-or-never: The case of interactive repair phenomena. Behavioral and Brain Sciences, 39:e76--e76, Jan 2016. [ bib | DOI | .pdf ]
[28]
C Heinrichs, A McPherson, and ACM. Performance-led design of computationally generated audio for interactive applications. In PROCEEDINGS OF THE TENTH ANNIVERSARY CONFERENCE ON TANGIBLE EMBEDDED AND EMBODIED INTERACTION (TEI16), pages 697--700, 2016. [ bib | DOI | http ]
[29]
D HERREMANS and E Chew. Morpheus: Automatic music generation with recurrent pattern constraints and tension profiles. In IEEE TENCON. Singapore, Nov 2016. [ bib ]
[30]
D HERREMANS and E Chew. Tension ribbons: Quantifying and visualising tonal tension. In Second International Conference on Technologies for Music Notation and Representation, volume 2, pages 8--18. Cambridge, May 2016. [ bib ]
[31]
A Holzapfel and E Benetos. The sousta corpus: Beat-informed automatic transcription of traditional dance tunes. In 17th International Society for Music Information Retrieval Conference, pages 531--537. New York, USA, ISMIR, Aug 2016. [ bib | http ]
[32]
R Jack, T Stockman, A McPherson, and ACM. Navigation of pitch space on a digital musical instrument with dynamic tactile feedback. In PROCEEDINGS OF THE TENTH ANNIVERSARY CONFERENCE ON TANGIBLE EMBEDDED AND EMBODIED INTERACTION (TEI16), pages 3--11, 2016. [ bib | DOI | http ]
[33]
RH Jack, T Stockman, and A McPherson. Effect of latency on performer interaction and subjective quality assessment of a digital musical instrument. In ACM International Conference Proceeding Series, volume 04-06-October-2016, pages 116--123, Oct 2016. [ bib | DOI ]
[34]
N Jillings, BM DE MAN, D Moffat, JD Reiss, and R Stables. Web audio evaluation tool: A framework for subjective assessment of audio. In J Freeman, A Lerch, and M Paradis, editors, https://smartech.gatech.edu/handle/1853/54577/browse. Atlanta, GA, USA, Apr 2016. [ bib | http ]
[35]
Nicholas Jillings, Brecht De Man, David Moffat, and Joshua D. Reiss. Web audio evaluation tool: A framework for subjective assessment of audio. In Proc. 2nd Web Audio Conference. Web Audio Conference, April 2016. [ bib ]
[36]
K Kosta, R Ramirez, OF Bandtlow, and E Chew. Mapping between dynamic markings and performed loudness: A machine learning approach. Journal of Mathematics and Music, 10:149--172, Aug 2016. [ bib ]
[37]
G Lafay, M Lagrange, M Rossignol, E Benetos, and A Roebel. A morphological model for simulating acoustic scenes and its application to sound event detection. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 24:1854--1864, Oct 2016. [ bib | DOI | http ]
[38]
B LIANG, G fazekas, A mcpherson, and M sandler. Classification of piano pedaling techniques using gesture data from a non-intrusive measurement system. In DMRN+11: Digital Music Research Network Workshop Proceedings 2016. Centre for Digital Music, Queen Mary University of London, Centre for Digital Music, Queen Mary University of London, Dec 2016. [ bib | http ]
[39]
A Mazzoni and N Bryan-Kinns. Moody: Haptic sensations to enhance mood in film music. In DIS 2016 Companion - Proceedings of the 2016 ACM Conference on Designing Interactive Systems: Fuse, pages 21--24, Jun 2016. [ bib | DOI ]
[40]
A MCPHERSON, A Chamberlain, A Hazzard, S McGrath, and S Benford. Designing for exploratory play with a hackable digital musical instrument. In ACM Conference on Designing Interactive Systems. Brisbane, Australia, Jun 2016. [ bib | DOI ]
[41]
AP McPherson, RH Jack, and G Moro. Action-sound latency: Are our tools fast enough? In Proceedings of the International Conference on New Interfaces for Musical Expression, Brisbane, Queensland, Australia, July 11-15, 2016. Griffith University, South Bank, Brisbane, Queensland, Australia, Griffith University, Jul 2016. Licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). Copyright remains with the author(s). [ bib | http ]
[42]
A MEHRABI, S Dixon, and M Sandler. Towards a comprehensive dataset of vocal imitations of drum sounds. In 2nd AES Workshop on Intelligent Music Production, Sep 2016. [ bib ]
[43]
Lucas Mengual, David Moffat, and Joshua D. Reiss. Modal synthesis of weapon sounds. In Proc. Audio Engineering Society Conference: 61st International Conference: Audio for Games. Audio Engineering Society, 2016. [ bib ]
[44]
O Metatla, N Bryan-Kinns, T Stockman, and F Martin. Sonification of reference markers for auditory graphs: effects on non-visual estimation tasks. PeerJ Computer Science, 2, Apr 2016. [ bib ]
[45]
O Metatla, N Correia, F Martin, N Bryan-Kinns, and T Stockman. Tap the shapetones: Exploring the effects of crossmodal congruence in an audio-visual interface. pages 1055--1066, 2016. proceedings: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. [ bib ]
[46]
O Metatla, F Martin, A Parkinson, N Bryan-Kinns, T Stockman, and A Tanaka. Audio-haptic interfaces for digital audio workstations: A participatory design approach. Journal on Multimodal User Interfaces, 10:247--258, Sep 2016. [ bib | DOI ]
[47]
David Moffat and Joshua D. Reiss. Implementation and assessment of joint source separation and dereverberation. In Proc. Audio Engineering Society Conference: 60th International Conference: DREAMS (Dereverberation and Reverberation of Audio, Music, and Speech). Audio Engineering Society, 2016. [ bib ]
[48]
G MORO, A Bin, RH Jack, C Heinrichs, and AP McPherson. Making high-performance embedded instruments with bela and pure data. In International Conference on Live Interfaces. University of Sussex, University of Sussex, Jun 2016. This hands-on workshop introduces participants to Bela, an embedded platform for ultra-low latency audio and sensor processing. [ bib | .html ]
[49]
K O'Hanlon, MB Sandler, and IEEE. An iterative hard thresholding approach to l(0) sparse hellinger nmf. In 2016 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING PROCEEDINGS, pages 4737--4741, 2016. [ bib | http ]
[50]
K O'Hanlon, MB Sandler, and IEEE. Compositional chroma estimation using powered euclidean distance. In 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), pages 1237--1241, 2016. [ bib | http ]
[51]
M Panteli, E Benetos, and S Dixon. Automatic detection of outliers in world music collections. In Fourth International Conference on Analytical Approaches to World Music (AAWM 2016), Maria Panteli, Queen Mary University of London, School of Electronic Enginering and Computer Science, Mile End Road, London, E1 4NS, United Kingdom, Jun 2016. New York, USA. [ bib | http ]
[52]
M Panteli, E Benetos, and S Dixon. Learning a feature space for similarity in world music. In 17th International Society for Music Information Retrieval Conference, pages 538--544. New York, USA, ISMIR, Aug 2016. [ bib | http ]
[53]
MT PEARCE and E Schubert. A new look at musical expectancy: The veridical versus the general in the mental organization of music. In R Kronland-Martinet, M Aramaki, and S Ystad, editors, Music, Mind, and Embodiment, pages 358--370. Springer, 2016. [ bib | DOI ]
[54]
MT Pearce, DW Zaidel, O Vartanian, M Skov, H Leder, A Chatterjee, and M Nadal. Neuroaesthetics: The cognitive neuroscience of aesthetic experience. Perspectives on psychological science : a journal of the Association for Psychological Science, 11:265--279, Mar 2016. [ bib | DOI ]
[55]
E QUINTON, M Sandler, and S Dixon. Estimation of the reliability of multiple rhythm features extraction from a single descriptor. IEEE International Conference on Acoustics Speech and Signal Processing, Apr 2016. [ bib ]
[56]
J REISS. A meta-analysis of high resolution audio perceptual evaluation. Journal of the Audio Engineering Society, 64:364--379, Jun 2016. [ bib | DOI | www: ]
[57]
F RODRIGUEZ ALGARRA, BL Sturm, and H Maruri-Aguilar. Analysing scattering-based music content analysis systems: Where's the music? In 17th International Society for Music Information Retrieval Conference (ISMIR 2016). New York, NY, USA, Aug 2016. [ bib ]
[58]
FJ Rodriguez-Serrano, S Ewert, P Vera-Candeas, and M Sandler. A score-informed shift-invariant extension of complex matrix factorization for improving the separation of overlapped partials in music recordings. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Shanghai, China, 2016. [ bib ]
[59]
S Sigtia, E BENETOS, and S Dixon. An end-to-end neural network for polyphonic piano music transcription. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 24:927--939, May 2016. [ bib | DOI | http ]
[60]
Y Song, S Dixon, MT Pearce, and AR Halpern. Perceived and induced emotion responses to popular music: Categorical and dimensional models. Music Perception, 33:472--492, 2016. [ bib | DOI ]
[61]
R Stables, B De Man, S Enderby, JD Reiss, G Fazekas, and T Wilmering. Semantic description of timbral transformations in music production. In MM 2016 - Proceedings of the 2016 ACM Multimedia Conference, pages 337--341, Oct 2016. [ bib | DOI ]
[62]
AG STOCKMAN and D Al-Thani. Reflections on the research methods used in an investigation of cross-modal collaborative information seeking. In The 5th International Workshop onn Collaboration: Human-Centered Issues & Interactivity Design, as part of The 2016 International Conference on Collaboration Technologies and Systems, Florida, USA, October-November 2016. Florida, USA, Oct 2016. [ bib ]
[63]
DF STOWELL, LF Gill, and D Clayton. Detailed temporal structure of communication networks in groups of songbirds. Journal of the Royal Society Interface, 13, Jun 2016. [ bib | DOI ]
[64]
DF STOWELL, M Wood, Y Stylianou, and H Glotin. Bird detection in audio: A survey and a challenge. In IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2016. [ bib ]
[65]
BLT STURM. “horse” inside: Seeking causes of the behaviours of music content analysis systems. ACM Computers in Entertainment, 9(39), Dec 2016. OA Monitor Exercise. [ bib | DOI ]
[66]
A Subramanian, N Cunha, and D HERREMANS. Uma abordagem baseada em programação linear inteira para a geração de solos de guitarra. In XLVIII Simpósio Brasileiro de Pesquisa Operacional (SBPO). Vitoria, Brasil, Sep 2016. [ bib ]
[67]
C Sulyok, A MCPHERSON, and C Harte. Evolving the process of a virtual composer. Natural Computing, Jun 2016. [ bib | DOI ]
[68]
FS THALMANN, perez carillo, fazekas, wiggins, and sandler. The mobile audio ontology: Experiencing dynamic music objects on mobile devices. 2016. [ bib ]
[69]
L Theodorou, PGT Healey, and F Smeraldi. Exploring audience behaviour during contemporary dance performances. In ACM International Conference Proceeding Series, volume 05-06-July-2016, Jul 2016. [ bib | DOI ]
[70]
M TIAN and MARKB Sandler. Towards music structural segmentation across genres: Features, structural hypotheses and annotation principles. ACM Transactions on Intelligent Systems and Technology, Nov 2016. [ bib ]
[71]
Luca Turchet, David Moffat, Ana Tajadura-Jiménez, Joshua D. Reiss, and Tony Stockman. What do your footsteps sound like? an investigation on interactive footstep sounds adjustment. Applied Acoustics, 2016. "In Press". [ bib ]
[72]
JJ Valero-Mas, E Benetos, and JM Iñesta. Classification-based note tracking for automatic music transcription. In https://sites.google.com/site/musicmachinelearning16/proceedings, pages 61--65. Riva del Garda, Italy, Sep 2016. [ bib | http ]
[73]
A Volk, E Chew, EH Margulis, and C Anagnostopoulou. Music similarity: Concepts, cognition and computation. JOURNAL OF NEW MUSIC RESEARCH, 45:207--209, Sep 2016. [ bib | DOI | http ]
[74]
V Välimäki and J Reiss. All about audio equalization: Solutions and frontiers. Applied Sciences, 6:129--129, May 2016. [ bib | DOI ]
[75]
L Wang, TK Hon, JD Reiss, and A Cavallaro. An iterative approach to source counting and localization using two distant microphones. IEEE/ACM Transactions on Audio Speech and Language Processing, 24:1079--1093, Jun 2016. [ bib | DOI ]
[76]
L Wang, TK Hon, JD Reiss, and A Cavallaro. Self-localization of ad-hoc arrays using time difference of arrivals. IEEE Transactions on Signal Processing, 64:1018--1033, Feb 2016. [ bib | DOI ]
[77]
S Wang, S Ewert, and S Dixon. Robust and efficient joint alignment of multiple musical performances. IEEE/ACM Transactions on Audio Speech and Language Processing, 24:2132--2145, Nov 2016. [ bib | DOI ]
[78]
WJ WILKINSON, D stowell, and J reiss. Performable spectral synthesis via low-dimensional modelling and control mapping. In DMRN+11: Digital Music Research Network Workshop Proceedings 2016. Centre for Digital Music, Queen Mary University of London, Centre for Digital Music, Queen Mary University of London, Dec 2016. [ bib | http ]
[79]
T Wilmering, G Fazekas, and MB Sandler. Aufx-o: Novel methods for the representation of audio processing workflows. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 9982 LNCS, pages 229--237, Jan 2016. [ bib | DOI ]
[80]
L YANG, SAYID-KHALID Rajab, and E Chew. Ava: A graphical user interface for automatic vibrato and portamento detection and analysis. In the 42nd International Computer Music Conference. Utrecht, The Netherlands, Sep 2016. [ bib ]
[81]
L Zhang, Y Wu, and M BARTHET. A web application for audience participation in live music performance: The open symphony use case. In International Conference on New Interfaces for Musical Expression, Jul 2016. [ bib ]

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