Last modified 10 May 2025
Publications (1986-2025)
An overview of publications of researchers from the Music Cognition Group.
2025
Burchardt, L. S., Hoeschele, M., Honing, H., Large, E., Merker, B., & Schneider, J. (2025). Chapter 1: What is rhythm and how can we study it? Center for Open Science.
DOI
10.31219/osf.io/69v5a_v1
Finkensiep, C., Ericson, P., Klassmann, S., & Rohrmeier, M. (2025). Chord Types and Figuration: A Bayesian Learning Model of Extended Chord Profiles. Music & Science, 8.
DOI
10.1177/20592043241291661
ten Cate, C. J., & Honing, H. (2025). Precursors of music and language in animals. In The Oxford Handbook of Language and Music. Oxford University Press.
DOI
10.1093/oxfordhb/9780192894700.013.0026
2024
Bouwer, F. L., Háden, G. P., & Honing, H. (2024). Probing Beat Perception with Event-Related Potentials (ERPs) in Human Adults, Newborns, and Nonhuman Primates. In Advances in Experimental Medicine and Biology (pp. 227–256). Springer International Publishing.
DOI
10.1007/978-3-031-60183-5_13
Burgoyne, J. A., & Honing, H. (2024). Rasch models for quantifying the strength of musical memory and the feeling of knowing. https://sites.google.com/york.ac.uk/escom12/home
Corcoran, K., du Mérac, T. R., Johnson, F., Burgoyne, J. A., Honing, H., Ruderfer, D. M., Lense, M., & Gordon, R. L. (2024). Linking a musical memory gamified task to large-scale health data via electronic health records: A feasibility study in a clinic waiting room. https://neuromusic.fondazione-mariani.org
Dam, N. C. P., Honing, H., & Spierings, M. J. (2024). Artoo-Detoo: What imitating a Star Wars droid reveals on allospecific vocal imitation in parrots and starlings. Cold Spring Harbor Laboratory.
DOI
10.1101/2024.10.10.617563
Háden, G. P., Bouwer, F. L., Honing, H., & Winkler, I. (2024). Beat processing in newborn infants cannot be explained by statistical learning based on transition probabilities. Cognition, 243, 105670.
DOI
10.1016/j.cognition.2023.105670
Hiemstra, A., & Sadakata, M. (2024). Sentences used in the speech-to-song illusion: Comparisons of acoustic vowel space. Musicae Scientiae, 28(3), 520–538.
DOI
10.1177/10298649231224786
Li, J., rui Hsin-Lin, Wolf, A., & Lothwesen, K. (2024). Measuring musical sophistication in the Chinese general population: Validation and replication of the Simplified Chinese Gold-MSI. Musicae Scientiae, 28(2), 197–221.
DOI
10.1177/10298649231183264
Morris, L. J., Leger, R., Newman, M., Burgoyne, J. A., Groves, R., Mangal, N., & Lee, J. H. (2024). Human-AI music process: A dataset of AI-supported songwriting processes from the AI Song Contest. Proceedings of the 25th International Conference of the Society for Music Information Retrieval.
Ning, Z.-Y., Honing, H., van Mil, H., & ten Cate, C. (2024). The role of spectral features and song duration in zebra finch, Taeniopygia guttata, song recognition. Animal Behaviour, 212, 73–91.
DOI
10.1016/j.anbehav.2024.03.011
van der Weij, B., Pearce, M. T., & Honing, H. (2024). Computational Modeling of Rhythm Perception and the Role of Enculturation. In The Oxford Handbook of Music and Corpus Studies. Oxford University Press.
DOI
10.1093/oxfordhb/9780190945442.013.13
Vélez Vásquez, M., Pouw, C., Burgoyne, J. A., & Zuidema, W. (2024). Exploring the inner mechanisms of large generative music models. Proceedings of the 25th International Conference of the Society for Music Information Retrieval, 5–14.
2023
Baelemans, M. C. E., Vélez Vásquez, M. A., & Burgoyne, J. A. (2023, October). Defining Playability in Musical Performance: Cognitive Factors and Implications for Automated Song Difficulty Estimation. The 16th International Conference of Students of Systematic Musicology.
Bais, O. B., Bouwer, F. L., & Sadakata, M. (2023, August 24). Exact repetition is not needed for the Speech-to-song transformation.
Bouwer, F., Háden, G. P., & Honing, H. (2023). Probing beat perception with event-related potentials (ERPs) in human adults, newborns, and non-human primates. Center for Open Science.
DOI
10.31234/osf.io/azk9q
Bouwer, F. L., Damsma, A., Burgoyne, J. A., Grahn, J., Slagter, H. A., & Honing, H. (2023). Measuring rhythm and beat perception abilities: a comparison of often-used tests. 688.
Bouwer, F. L., Fahrenfort, J. J., Millard, S. K., Kloosterman, N. A., & Slagter, H. A. (2023). A Silent Disco: Differential Effects of Beat-based and Pattern-based Temporal Expectations on Persistent Entrainment of Low-frequency Neural Oscillations. Journal of Cognitive Neuroscience, 35(6), 990–1020.
DOI
10.1162/jocn_a_01985
Burgoyne, J. A., Baker, D. J., & Honing, H. (2023). What a game can reveal about music perception: A psychometric analysis of the matching pairs game.
Cecchetti, G., Finkensiep, C., Guan, X., Herff, S. A., Fiveash, A., Pelofi, C., & Drury, J. E. (2023). Music Cognition between Theory and Experiment. 38–39. https://cognitivesciencesociety.org/cogsci-2023/
Chittar, C. R., Jang, H., Samuni, L., Lewis, J., Honing, H., Loon, E. E. van, & Janmaat, K. R. L. (2023). Music production and its role in coalition signaling during foraging contexts in a hunter-gatherer society. Frontiers in Psychology, 14.
DOI
10.3389/fpsyg.2023.1218394
Christoph Finkensiep, Matthieu Haeberle, Friedrich Eisenbrand, Markus Neuwirth, & Martin Rohrmeier. (2023). Repetition-Structure Inference With Formal Prototypes. ISMIR.
DOI
10.5281/ZENODO.10265304
Damsma, A., Bazin, P. L. E. A., Kaplan, T., Honing, H., & Bouwer, F. L. (2023). Modelling Flexible Rhythm Prediction in Continuous Time.
Damsma, A., Bouwer, F. L., Kemp, S. A., Grahn, J., Honing, H., & Bazin, P. L. E. A. (2023). Exploring Individual Differences in Structural Connectivity Underlying Rhythmic Abilities.
Eagle, O. M., Mendoza, J. K., Wolf, J. E., Baker, D. J., & Vuvan, D. T. (2023a). Anti-Racism and Equity Panel: How Can Music Science Be More Socially Just? Center for Open Science.
DOI
10.31234/osf.io/qjfpe
Eagle, O. M., Mendoza, J. K., Wolf, J. E., Baker, D. J., & Vuvan, D. T. (2023b). Anti-Racism and Equity Panel: How Can Music Science Be More Socially Just? Auditory Perception & Cognition, 6(3–4), 369–386.
DOI
10.1080/25742442.2023.2236540
Fiveash, A., Ferreri, L., Bouwer, F. L., Kösem, A., Moghimi, S., Ravignani, A., Keller, P. E., & Tillmann, B. (2023). Can rhythm-mediated reward boost learning, memory, and social connection? Perspectives for future research. Neuroscience & Biobehavioral Reviews, 149, 105153.
DOI
10.1016/j.neubiorev.2023.105153
Hiemstra, A., & Sadakata, M. (2023). Examining the Interaction Between Motor Development and Early Violin Learning. String Research Journal, 14(1), 23–39.
DOI
10.1177/19484992231195014
Honing, H. (2023a). Comparative Research on Beat and Isochrony Perception in Primates. 90.
Honing, H. (2023b). Unravelling our capacity for music. Open Science Framework.
DOI
10.17605/OSF.IO/YXFV4
Honing, H. (2023c). Comparative Research on Beat and Isochrony Perception in Primates. https://jsmpc.org/ICMPC17/news/e-proceedings/
Huang, X., Burgoyne, J. A., & Honing, H. (2023). What makes Chinese music memorable to the Chinese? The relationship between familiarity and recognition.
Janssen, B., Burgoyne, J. A., Janulevicius, A., Rot, E., & Honing, H. (2023). An infrastructure for reusable online music experiments. 366.
John Ashley Burgoyne, Janne Spijkervet, & David John Baker. (2023). Measuring the Eurovision Song Contest: A Living Dataset for Real-World MIR. ISMIR.
DOI
10.5281/ZENODO.10265415
Li, J., Baker, D. J., Burgoyne, J. A., & Honing, H. (2023). Is Pitch Information Indispensable for Music Recognition? A Pilot Study Based on a Musical Matching Pairs Game. In M. Tsuzaki, M. Sadakata, S. Ikegami, T. Matsui, M. Okano, & H. Shoda (Eds.), The e-proceedings of the 17th International Conference on Music Perception and Cognition and the 7th Conference of the Asia-Pacific Society for the Cognitive Sciences of Music (pp. 65–71). The Japanese Society for Music Perception.
Marcel A. Vélez Vásquez, Mariëlle Baelemans, Jonathan Driedger, Willem Zuidema, & John Ashley Burgoyne. (2023). Quantifying the Ease of Playing Song Chords on the Guitar. ISMIR.
DOI
10.5281/ZENODO.10265391
Neuwirth, M., Finkensiep, C., & Rohrmeier, M. (2023). Musical Schemata: Modelling Challenges and Pattern Finding (BachBeatles). In Digital Humanities Research (pp. 147–164). Bielefeld University Press / transcript Verlag.
DOI
10.14361/9783839469132-016
Ning, Z.-Y., Honing, H., & ten Cate, C. (2023). Zebra finches (Taeniopygia guttata) demonstrate cognitive flexibility in using phonology and sequence of syllables in auditory discrimination. Animal Cognition, 26(4), 1161–1175.
DOI
10.1007/s10071-023-01763-4
Sadakata, M., Weidema, J. L., Roncaglia-Denissen, M. P. M., & Honing, H. (2023). Correction: Parallel pitch processing in speech and melody: A study of the interference of musical melody on lexical pitch perception in speakers of Mandarin. PLOS ONE, 18(3), e0283262.
DOI
10.1371/journal.pone.0283262
Scarratt, R. J., Heggli, O. A., Vuust, P., & Sadakata, M. (2023). Music that is used while studying and music that is used for sleep share similar musical features, genres and subgroups. Scientific Reports, 13(1).
DOI
10.1038/s41598-023-31692-8
Spierings, M. J., Dam, N., & Honing, H. (2023). Bird Singalong Project.
2022
Baker, D. J., Li, J., Burgoyne, J. A., & Honing, H. (2022). Would You Like to Participate? Prospects and Pitfalls of Designing Engaging and Intrinsically Motivating Experiments.
Bouwer, F. L. (2022). Neural Entrainment to Auditory Rhythms: Automatic or Top-Down Driven? The Journal of Neuroscience, 42(11), 2146–2148.
DOI
10.1523/jneurosci.2305-21.2022
Cate, C. ten, & Honing, H. (2022). Precursors of Music and Language in Animals. Center for Open Science.
DOI
10.31234/osf.io/4zxtr
Cecchetti, G., Herff, S. A., Finkensiep, C., Harasim, D., & Rohrmeier, M. A. (2022). Hearing functional harmony in jazz: A perceptual study of music-theoretical accounts of extended tonality. Musicae Scientiae, 27(3), 672–697.
DOI
10.1177/10298649221122245
Damsma, A., de Roo, M., Doelling, K., Bazin, P. L. E. A., & Bouwer, F. L. (2022). Tempo-Dependent Changes in Neural Responses to Rhythm as a Marker of Entrainment.
Honing, H., Bouwer, F. L., Burgoyne, J. A., Sadakata, M., Damsma, A., Baelemans, M. C. E., Janssen, B. D., & Young, Z. (2022). ToontjeHoger: ToontjeHoger is een website met spelletjes die de luisteraar laat inzien dat zij muzikaler is dan je zou denken.
Huang, X., Burgoyne, J. A., & Honing, H. (2022a). The Structure of Musical Preferences Using Chinese Samples.
Huang, X., Burgoyne, J. A., & Honing, H. (2022b). What We Remember is the Prototypical: Pop Music in China from the 1970s to 2010s.
Li, J., Baker, D. J., Burgoyne, J. A., & Honing, H. (2022). The Possibilities and Impossibilities of the Matching-Pairs Game for Music Cognition Research — An Evaluation of a Case Study.
Ning, Z.-Y., Honing, H., & Cate, C. ten. (2022). Zebra finches (Taeniopygia guttata) demonstrate cognitive flexibility in using phonology and sequence of syllables in auditory discrimination. Research Square Platform LLC.
DOI
10.21203/rs.3.rs-2247248/v1
Sadakata, M., Yamaguchi, Y., Ohsawa, C., Matsubara, M., Terasawa, H., von Schnehen, A., Müllensiefen, D., & Sekiyama, K. (2022). The Japanese translation of the Gold-MSI: Adaptation and validation of the self-report questionnaire of musical sophistication. Musicae Scientiae, 27(3), 798–810.
DOI
10.1177/10298649221110089
Shanahan, D., Burgoyne, J. A., & Quinn, I. (Eds.). (2022). The Oxford Handbook of Music and Corpus Studies. Oxford University Press.
DOI
10.1093/oxfordhb/9780190945442.001.0001
Vásquez, M. A. V., & Burgoyne, J. A. (2022). Tailed U-Net: Multi-Scale Music Representation Learning. Zenodo.
DOI
10.5281/ZENODO.7316596
Yamashita, M., Ohsawa, C., Suzuki, M., Guo, X., Sadakata, M., Otsuka, Y., Asano, K., Abe, N., & Sekiyama, K. (2022). Neural Advantages of Older Musicians Involve the Cerebellum: Implications for Healthy Aging Through Lifelong Musical Instrument Training. Frontiers in Human Neuroscience, 15.
DOI
10.3389/fnhum.2021.784026
2021
Bouwer, F. L., Nityananda, V., Rouse, A. A., & ten Cate, C. (2021). Rhythmic abilities in humans and non-human animals: a review and recommendations from a methodological perspective. Philosophical Transactions of the Royal Society B: Biological Sciences, 376(1835).
DOI
10.1098/rstb.2020.0335
Burgoyne, J. A., & Koops, H. V. (2021). We are Not Groupies⋯ We are Band Aids’: Assessment Reliability in the AI Song Contest. Transactions of the International Society for Music Information Retrieval, 4(1), 236.
DOI
10.5334/tismir.102
Chen, A., Çetinçelik, M., Roncaglia-Denissen, M. P., & Sadakata, M. (2021). Native language, L2 experience, and pitch processing in music. Linguistic Approaches to Bilingualism, 13(2), 218–237. Portico.
DOI
10.1075/lab.20030.che
Cornelissen, B. J. M., Zuidema, W. H., & Burgoyne, J. A. (2021, November 3). Catafolk: Cataloguing folk music datasets for comparative musicology. https://sites.google.com/view/sysmus21/home?authuser=0
Cornelissen, B., Zuidema, W., & Burgoyne, J. A. (2021). Cosine Contours: a Multipurpose Representation for Melodies. Zenodo.
DOI
10.5281/ZENODO.5624531
Damsma, A., Schlichting, N., & van Rijn, H. (2021). Temporal Context Actively Shapes EEG Signatures of Time Perception. The Journal of Neuroscience, 41(20), 4514–4523.
DOI
10.1523/jneurosci.0628-20.2021
Damsma, A., Schlichting, N., van Rijn, H., & Roseboom, W. (2021). Estimating Time: Comparing the Accuracy of Estimation Methods for Interval Timing. Collabra: Psychology, 7(1).
DOI
10.1525/collabra.21422
Finkensiep, C., & Rohrmeier, M. A. (2021). Modeling and Inferring Proto-Voice Structure in Free Polyphony. Zenodo.
DOI
10.5281/ZENODO.5624430
Goltz, F., & Sadakata, M. (2021). Do you listen to music while studying? A portrait of how people use music to optimize their cognitive performance. Acta Psychologica, 220, 103417.
DOI
10.1016/j.actpsy.2021.103417
Greenfield, M. D., Honing, H., Kotz, S. A., & Ravignani, A. (2021). Synchrony and rhythm interaction: from the brain to behavioural ecology. Philosophical Transactions of the Royal Society B: Biological Sciences, 376(1835).
DOI
10.1098/rstb.2020.0324
Harasim, D., Finkensiep, C., Bigo, L., Giraud, M., Levé, F., Shanahan, D., Sears, D. R. W., & Rohrmeier, M. (2021). Music Cognition: The Complexity of Musical Structure. 35–36.
Herff, S. A., Harasim, D., Cecchetti, G., Finkensiep, C., & Rohrmeier, M. A. (2021). Hierarchical syntactic structure predicts listeners’ sequence completion in music. 43rd Annual Meeting of the Cognitive Science Society (CogSci 2021), 3, 903–909.
Honing, H. (2021a). Unravelling the origins of musicality: Beyond music as an epiphenomenon of language. Behavioral and Brain Sciences, 44.
DOI
10.1017/s0140525x20001211
Honing, H. (2021b). Music Cognition. Routledge.
DOI
10.4324/9781003158301
Honing, H. (2021c). Lured Into Listening. Zeitschrift Für Psychologie, 229(4), 266–268.
DOI
10.1027/2151-2604/a000474
Honing, H., & Cornelissen, B. (2021). What is your position in the BBS discussion on the origins of music/ality? Music Matters.
Kuiper, L., Orken, A., & Burgoyne, J. A. (2021). It’s Beginning to Sound a Lot Like Christmas: Exploring Short- and Long-Term Memory of Christmas Music through an Online Game.
Michalko, A., & Burgoyne, J. A. (2021). Description of Flute Tone Quality: Semantic Labelling of Low-Level Features.
Slagter, H. A., & Bouwer, F. L. (2021). Qualitative Versus Quantitative Individual Differences in Cognitive Neuroscience. Journal of Cognition, 4(1).
DOI
10.5334/joc.170
Spijkervet, J., & Burgoyne, J. A. (2021). Contrastive Learning of Musical Representations. Zenodo.
DOI
10.5281/ZENODO.5624573
Terasawa, H., Matsubara, M., Goudarzi, V., & Sadakata, M. (2021). Music in Quarantine: Connections Between Changes in Lifestyle, Psychological States, and Musical Behaviors During COVID-19 Pandemic. Frontiers in Psychology, 12.
DOI
10.3389/fpsyg.2021.689505
2020
Bouwer, F. L., Honing, H., & Slagter, H. A. (2020). Beat-based and Memory-based Temporal Expectations in Rhythm: Similar Perceptual Effects, Different Underlying Mechanisms. Journal of Cognitive Neuroscience, 32(7), 1221–1241.
DOI
10.1162/jocn_a_01529
Cecchetti, G., Herff, S. A., Finkensiep, C., & Rohrmeier, M. A. (2020). The experience of musical structure as computation : what can we learn? [JD]. Rivista Di Analisi e Teoria Musicale : XXVI, 2, 2020, 2.
DOI
10.53152/1032
Cornelissen, B., Zuidema, W., & Burgoyne, J. A. (2020a). Mode classification and natural units in plainchant.
DOI
10.5281/ZENODO.4245572
Cornelissen, B., Zuidema, W., & Burgoyne, J. A. (2020b). Studying Large Plainchant Corpora Using chant21. 7th International Conference on Digital Libraries for Musicology, 40–44.
DOI
10.1145/3424911.3425514
Finkensiep, C., Déguernel, K., Neuwirth, M., & Rohrmeier, M. (2020). Voice-leading schema recognition using rhythm and pitch features.
DOI
10.5281/ZENODO.4245482
Harasim, D., Finkensiep, C., Ericson, P., O’Donnell, T. J., & Rohrmeier, M. (2020). The jazz Harmony Treebank.
DOI
10.5281/ZENODO.4245406
Honing, H. (2020a). Are humans the only musical species? The MIT Press Reader.
Honing, H. (2020b). La scimmia batte il tempo: Alle origini della musicalità negli animali e nell’uomo. Carocci Editore.
Jacoby, N., Margulis, E. H., Clayton, M., Hannon, E., Honing, H., Iversen, J., Klein, T. R., Mehr, S. A., Pearson, L., Peretz, I., Perlman, M., Polak, R., Ravignani, A., Savage, P. E., Steingo, G., Stevens, C. J., Trainor, L., Trehub, S., Veal, M., & Wald-Fuhrmann, M. (2020). Cross-Cultural Work in Music Cognition. Music Perception, 37(3), 185–195.
DOI
10.1525/mp.2020.37.3.185
Nieuwenhuijsen, A. N. V., Burgoyne, J. A., Wiering, F., & Sneekes, M. (2020). A simple method for user-driven music thumbnailing.
DOI
10.5281/ZENODO.4245410
Polydorou, D., Ben-Tal, O., Damsma, A., & Schlichting, N. (2020). VR: Time Machine. In Lecture Notes in Computer Science (pp. 294–306). Springer International Publishing.
DOI
10.1007/978-3-030-49065-2_21
Sadakata, M., Weidema, J. L., & Honing, H. (2020). Parallel pitch processing in speech and melody: A study of the interference of musical melody on lexical pitch perception in speakers of Mandarin. PLOS ONE, 15(3), e0229109.
DOI
10.1371/journal.pone.0229109
van der Mijn, R., Damsma, A., Taatgen, N., & van Rijn, H. (2020). Individual optimization of risky decisions in duration and distance estimations. Attention, Perception, & Psychophysics, 83(4), 1897–1906.
DOI
10.3758/s13414-020-02225-6
2019
Damsma, A., Taatgen, N., de Jong, R., & van Rijn, H. (2019). No evidence for an attentional bias towards implicit temporal regularities. Attention, Perception, & Psychophysics, 82(3), 1136–1149.
DOI
10.3758/s13414-019-01851-z
Finkensiep, C., Widdess, R., & Rohrmeier, M. (2019). Modelling the Syntax of North Indian Melodies with a Generalized Graph Grammar.
DOI
10.5281/ZENODO.3527844
Groenveld, G., Burgoyne, J. A., & Sadakata, M. (2019). I still hear a melody: investigating temporal dynamics of the Speech-to-Song Illusion. Psychological Research, 84(5), 1451–1459.
DOI
10.1007/s00426-018-1135-z
Hallez, Q., Damsma, A., Rhodes, D., van Rijn, H., & Droit-Volet, S. (2019). The dynamic effect of context on interval timing in children and adults. Acta Psychologica, 192, 87–93.
DOI
10.1016/j.actpsy.2018.10.004
Honing, H. (2019a). The Evolving Animal Orchestra: In Search of What Makes Us Musical . The MIT Press.
Honing, H. (2019b). How playing music for rhesus monkeys is teaching us about our own brains. Salon .
Honing, H. (2019c). What makes music special to us: Clarifying the differences between what animals and humans hear. Nautilus, 70(2).
Honing, H. (2019d). Muziek is echt geen wondermiddel. Trouw.
Honing, H. (2019e). Der Affe Schlägt den Takt: Musikalität bei Tier und Mensch. Eine Spurensuche. Henschel Verlag.
Honing, H., & Bouwer, F. L. (2019). Rhythm. In P. J. Rentfrow & D. J. Levitin (Eds.), Foundations in Music Psychology (pp. 33–69). The MIT Press.
Koops, H. V., de Haas, W. B., Burgoyne, J. A., Bransen, J., Kent-Muller, A., & Volk, A. (2019). Annotator subjectivity in harmony annotations of popular music. Journal of New Music Research, 48(3), 232–252.
DOI
10.1080/09298215.2019.1613436
2018
Bouwer, F. L., Burgoyne, J. A., Odijk, D., Honing, H., & Grahn, J. A. (2018). What makes a rhythm complex? The influence of musical training and accent type on beat perception. PLOS ONE, 13(1), e0190322.
DOI
10.1371/journal.pone.0190322
Damsma, A., van der Mijn, R., & van Rijn, H. (2018). Neural markers of memory consolidation do not predict temporal estimates of encoded items. Neuropsychologia, 117, 36–45.
DOI
10.1016/j.neuropsychologia.2018.04.039
Finkensiep, C., Neuwirth, M., & Rohrmeier, M. (2018). Generalized Skipgrams for Pattern Discovery in Polyphonic Streams.
DOI
10.5281/ZENODO.1492473
Gingras, B., Honing, H., Peretz, I., Trainor, L. J., & Fisher, S. E. (2018). Defining the Biological Bases of Individual Differences in Musicality. In The Origins of Musicality (pp. 221–250). The MIT Press.
DOI
10.7551/mitpress/10636.003.0015
Honing, H. (2018a). Aap slaat maat: Op zoek naar de oorsprong van muzikaliteit bij mens en dier. Nieuw Amsterdam.
Honing, H. (2018b). Musicality as an upbeat to music: Introduction and research agenda. In H. Honing (Ed.), The Origins of Musicality (pp. 3–20). MIT Press.
Honing, H. (Ed.). (2018c). The Origins of Musicality. The MIT Press.
Honing, H. (2018d). On the biological basis of musicality. Annals of the New York Academy of Sciences, 1423(1), 51–56. Portico.
DOI
10.1111/nyas.13638
Honing, H., Bouwer, F. L., Prado, L., & Merchant, H. (2018). Rhesus Monkeys (Macaca mulatta) Sense Isochrony in Rhythm, but Not the Beat: Additional Support for the Gradual Audiomotor Evolution Hypothesis. Frontiers in Neuroscience, 12.
DOI
10.3389/fnins.2018.00475
Jaschke, A. C., Honing, H., & Scherder, E. J. A. (2018a). Longitudinal Analysis of Music Education on Executive Functions in Primary School Children. Frontiers in Neuroscience, 12.
DOI
10.3389/fnins.2018.00103
Jaschke, A. C., Honing, H., & Scherder, E. J. A. (2018b). Exposure to a musically-enriched environment; Its relationship with executive functions, short-term memory and verbal IQ in primary school children. PLOS ONE, 13(11), e0207265.
DOI
10.1371/journal.pone.0207265
Roncaglia-Denissen, M. P., Bouwer, F. L., & Honing, H. (2018). Decision Making Strategy and the Simultaneous Processing of Syntactic Dependencies in Language and Music. Frontiers in Psychology, 9.
DOI
10.3389/fpsyg.2018.00038
Schlichting, N., Damsma, A., Aksoy, E. E., Wächter, M., Asfour, T., & van Rijn, H. (2018). Temporal Context Influences the Perceived Duration of Everyday Actions: Assessing the Ecological Validity of Lab-Based Timing Phenomena. Journal of Cognition, 2(1).
DOI
10.5334/joc.4
Smit, E. A., & Sadakata, M. (2018). The effect of handedness on spatial and motor representation of pitch patterns in pianists. PLOS ONE, 13(5), e0195831.
DOI
10.1371/journal.pone.0195831
Thorin, J., Sadakata, M., Desain, P., & McQueen, J. M. (2018). Perception and production in interaction during non-native speech category learning. The Journal of the Acoustical Society of America, 144(1), 92–103.
DOI
10.1121/1.5044415
2017
Damsma, A., & van Rijn, H. (2017). Pupillary response indexes the metrical hierarchy of unattended rhythmic violations. Brain and Cognition, 111, 95–103.
DOI
10.1016/j.bandc.2016.10.004
Honing, H. (2017). Wat is een absoluut gehoor en is het erfelijk? In B. de Graaf & A. Rinnooy Kan (Eds.), Hoe zwaar is licht (pp. 74–76). Uitgeverij Balans.
Janssen, B., Burgoyne, J. A., & Honing, H. (2017). Predicting Variation of Folk Songs: A Corpus Analysis Study on the Memorability of Melodies. Frontiers in Psychology, 8.
DOI
10.3389/fpsyg.2017.00621
Korsmit, I. R., Burgoyne, J. A., & Honing, H. (2017). If You Wanna Be My Lover … A Hook Discovery Game to Uncover Individual Differences in Long-term Musical Memory. In E. Van Dijck (Ed.), Proceedings of the 25th Anniversary Conference of the European Society for the Cognitive Sciences of Music (pp. 106–111). Ghent University.
Mooren, N., Burgoyne, J. A., & Honing, H. (2017). Investigating grouping behaviour of dancers in a silent disco using overhead video capture. In E. Van Dijck (Ed.), Proceedings of the 25th Anniversary Conference of the European Society for the Cognitive Sciences of Music (pp. 142–149). Ghent University.
Ravignani, A., Honing, H., & Kotz, S. A. (2017). Editorial: The Evolution of Rhythm Cognition: Timing in Music and Speech. Frontiers in Human Neuroscience, 11.
DOI
10.3389/fnhum.2017.00303
van der Weij, B., Pearce, M. T., & Honing, H. (2017). A Probabilistic Model of Meter Perception: Simulating Enculturation. Frontiers in Psychology, 8.
DOI
10.3389/fpsyg.2017.00824
Vaquero Patricio, C., Titov, I., & Honing, H. (2017, July 31). What score markings can say of the synergy between expressive timing and loudness.
2016
Bouwer, F. L. (2016). What do we need to hear a beat? The influence of attention, musical abilities, and accents on the perception of metrical rhythm [Phdthesis]. Universiteit van Amsterdam.
Bouwer, F. L., Werner, C. M., Knetemann, M., & Honing, H. (2016). Disentangling beat perception from sequential learning and examining the influence of attention and musical abilities on ERP responses to rhythm. Neuropsychologia, 85, 80–90.
DOI
10.1016/j.neuropsychologia.2016.02.018
Cornelissen, B., Sadakata, M., & Honing, H. (2016). Categorization in the Speech to Song Transformation (STS). Proceedings of the 14th International Conference on Music Perception and Cognition, 386.
Honing, H. (2016a). Voor de muziek uit. Waarom muzikaliteit aan muziek én taal voorafgaat. Onze Taal, 85(2/3), 8.
Honing, H. (2016b). Muzikaliteit gaat aan muziek én taal vooraf. BLIND : Interdisciplinair Tijdschrift, 43.
Mathias, B., Lidji, P., Honing, H., Palmer, C., & Peretz, I. (2016). Electrical Brain Responses to Beat Irregularities in Two Cases of Beat Deafness. Frontiers in Neuroscience, 10.
DOI
10.3389/fnins.2016.00040
Roncaglia-Denissen, M. P., Roor, D. A., Chen, A., & Sadakata, M. (2016). The Enhanced Musical Rhythmic Perception in Second Language Learners. Frontiers in Human Neuroscience, 10.
DOI
10.3389/fnhum.2016.00288
ten Cate, C., Spierings, M., Hubert, J., & Honing, H. (2016). Can Birds Perceive Rhythmic Patterns? A Review and Experiments on a Songbird and a Parrot Species. Frontiers in Psychology, 7.
DOI
10.3389/fpsyg.2016.00730
Weidema, J. L., Roncaglia-Denissen, M. P., & Honing, H. (2016). Top–Down Modulation on the Perception and Categorization of Identical Pitch Contours in Speech and Music. Frontiers in Psychology, 7.
DOI
10.3389/fpsyg.2016.00817
2015
Balen, J. V., Burgoyne, J. A., Bountouridis, D., Müllensiefen, D., & Veltkamp, R. C. (2015). Corpus Analysis Tools For Computational Hook Discovery. Zenodo.
DOI
10.5281/ZENODO.1415038
Bouwer, F. L., & Honing, H. (2015). Temporal attending and prediction influence the perception of metrical rhythm: evidence from reaction times and ERPs. Frontiers in Psychology, 6.
DOI
10.3389/fpsyg.2015.01094
Burgoyne, J. A., Fujinaga, I., & Downie, J. S. (2015). Music Information Retrieval. In A New Companion to Digital Humanities (pp. 213–228). Wiley; Portico.
DOI
10.1002/9781118680605.ch15
Burgoyne, J. A., Hofman, A., van der Maas, H., & Honing, H. (2015). Adaptive music recognition games for dementia therapy. In J. Ginsborg, A. Lamont, & S. Bramley (Eds.), Escom Manchester 2015 (pp. 264–265). ESCOM.
Gingras, B., Honing, H., Peretz, I., Trainor, L. J., & Fisher, S. E. (2015). Defining the biological bases of individual differences in musicality. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1664), 20140092.
DOI
10.1098/rstb.2014.0092
Háden, G. P., Honing, H., Török, M., & Winkler, I. (2015). Detecting the temporal structure of sound sequences in newborn infants. International Journal of Psychophysiology, 96(1), 23–28.
DOI
10.1016/j.ijpsycho.2015.02.024
Honing, H. (2015a). Do re mi (Interview). In G. Schilling (Ed.), Een aap die kan blozen (pp. 62–70). Fontaine.
Honing, H. (2015b). Een intieme relatie met emoties en geheugen (interview). In R. van Boxtel (Ed.), Van trilling tot rilling (pp. 58–70). Prometheus | Bert Bakker.
Honing, H., ten Cate, C., Peretz, I., & Trehub, S. E. (2015). Without it no music: cognition, biology and evolution of musicality. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1664), 20140088.
DOI
10.1098/rstb.2014.0088
Olthof, M., Janssen, B., & Honing, H. (2015). The Role of Absolute Pitch Memory in the Oral Transmission of Folksongs. Empirical Musicology Review, 10(3), 161–174.
DOI
10.18061/emr.v10i3.4435
Schaefer, R. S., Beijer, L. J., Seuskens, W., Rietveld, T. C. M., & Sadakata, M. (2015). Intuitive visualizations of pitch and loudness in speech. Psychonomic Bulletin & Review, 23(2), 548–555.
DOI
10.3758/s13423-015-0934-0
van der Aa, J., Honing, H., & ten Cate, C. (2015). The perception of regularity in an isochronous stimulus in zebra finches (Taeniopygia guttata) and humans. Behavioural Processes, 115, 37–45.
DOI
10.1016/j.beproc.2015.02.018
Willems, C., Damsma, A., Wierda, S. M., Taatgen, N., & Martens, S. (2015). Training-induced Changes in the Dynamics of Attention as Reflected in Pupil Dilation. Journal of Cognitive Neuroscience, 27(6), 1161–1171.
DOI
10.1162/jocn_a_00767
2014
Aljanaki, A., Bountouridis, D., Burgoyne, J. A., Van Balen, J., Wiering, F., Honing, H., & Veltkamp, R. (2014). Designing Games with a Purpose for Data Collection in Music Research. Emotify and Hooked: Two Case Studies. In Lecture Notes in Computer Science (pp. 29–40). Springer International Publishing.
DOI
10.1007/978-3-319-12157-4_3
Bouwer, F. L. (2014). Neural oscillations as an index of metrical structure in a non-isochronous rhythm.
Bouwer, F. L., Van Zuijen, T. L., & Honing, H. (2014). Beat Processing Is Pre-Attentive for Metrically Simple Rhythms with Clear Accents: An ERP Study. PLoS ONE, 9(5), e97467.
DOI
10.1371/journal.pone.0097467
Burgoyne, J. A., de Haas, W. B., & Pauwels, J. (2014). On comparative statistics for labelling tasks: What can we learn from MIREX ACE 2013? In H.-M. Wang, Y.-H. Yang, & J. H. Lee (Eds.), Proceedings of the 15th International Society for Music Information Retrieval Conference (pp. 525–530). ISMIR.
Honing, H. (2014a). Musical cognition: A science of listening : with a new afterword by the author. Transaction Publishers.
Honing, H. (2014b). Iedereen is muzikaal (public website).
Honing, H. (2014c). Gaan we de kinderen weer horen zingen in de klas? Volkskrant (Opinie & Debat), 22.
Honing, H., Bouwer, F. L., & Háden, G. P. (2014). Perceiving Temporal Regularity in Music: The Role of Auditory Event-Related Potentials (ERPs) in Probing Beat Perception. In Advances in Experimental Medicine and Biology (pp. 305–323). Springer New York.
DOI
10.1007/978-1-4939-1782-2_16
Honing, H., & Levelt, W. J. M. (2014). Je hoeft niet in wetenschap te geloven. NRC Handelsblad.
DOI
https://www.nrc.nl/nieuws/2014/05/20/denkennrcnl-1378914-a250985
Honing, H., & Merchant, H. (2014). Differences in auditory timing between human and nonhuman primates. Behavioral and Brain Sciences, 37(6), 557–558.
DOI
10.1017/s0140525x13004056
Honing, H., & Zuidema, W. (2014). Decomposing dendrophilia. Physics of Life Reviews, 11(3), 375–376.
DOI
10.1016/j.plrev.2014.06.020
Honingh, A. K., Burgoyne, J. A., van Kranenburg, P., & Volk, A. (2014). Strengthening Interdisciplinarity in MIR: Four Examples of Using MIR Tools for Musicology (WorkingPaper PP-2014-18; Institute for Logic, Language, and Computation). University of Amsterdam.
Merchant, H., & Honing, H. (2014). Are non-human primates capable of rhythmic entrainment? Evidence for the gradual audiomotor evolution hypothesis. Frontiers in Neuroscience, 7.
DOI
10.3389/fnins.2013.00274
Patricio, C. V., & Honing, H. (2014). Generating expressive timing by combining rhythmic categories and Lindenmayer systems. AISB 2014 - 50th Annual Convention of the AISB.
Rouinfar, A., Agra, E., Larson, A. M., Rebello, N. S., & Loschky, L. C. (2014). Linking attentional processes and conceptual problem solving: visual cues facilitate the automaticity of extracting relevant information from diagrams. Frontiers in Psychology, 5.
DOI
10.3389/fpsyg.2014.01094
Sadakata, M., & McQueen, J. M. (2014). Individual aptitude in Mandarin lexical tone perception predicts effectiveness of high-variability training. Frontiers in Psychology, 5.
DOI
10.3389/fpsyg.2014.01318
Sadakata, M., Shingai, M., Sulpizio, S., Brandmeyer, A., & Sekiyama, K. (2014). Language specific listening of Japanese geminate consonants: a cross-linguistic study. Frontiers in Psychology, 5.
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10.3389/fpsyg.2014.01422
van Balen, J., Karavellas, T., Burgoyne, J. A., Wiering, F., Bountouridis, D., & Honing, H. (2014). Modeling Music and Memory Using Information Retrieval Techniques and Games with a Purpose.
Weidema, J. L., Roncaglia-Denissen, M. P., & Honing, H. (2014). The effect of musical pitch on the perception of lexical pitch in speakers of Madarin. 172.
2013
Brandmeyer, A., Sadakata, M., Spyrou, L., McQueen, J. M., & Desain, P. (2013). Decoding of single-trial auditory mismatch responses for online perceptual monitoring and neurofeedback. Frontiers in Neuroscience, 7.
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10.3389/fnins.2013.00265
Burgoyne, J. A. (2013). On the Dimensionality of Music Similarity. 24.
Burgoyne, J. A., Bountouridis, D., Van Balen, J., & Honing, H. (2013). Hooked: A Game for Discovering What Makes Music Catchy. In A. de Souza Britto Jr., F. Gouyon, & S. Dixon (Eds.), Proceedings of the 14th International Society for Music Information Retrieval Conference (pp. 245–250). ISMIR.
Burgoyne, J. A., & Honing, H. (2013a). Does MIR Need to be More Catchy? http://www.cogmir.org/2013-seminar/
Burgoyne, J. A., Wild, J., & Fujinaga, I. (2013). Compositional Data Analysis of Harmonic Structures in Popular Music. In Lecture Notes in Computer Science (pp. 52–63). Springer Berlin Heidelberg.
DOI
10.1007/978-3-642-39357-0_4
Dannenberg, R. B., Desain, P., & Honing, H. (2013). Programming language design for music. Musical Signal Processing, 271–315.
Honing, H. (2013a). Sin eso no hay música: La inducción del beat como un rasgo musical fundamental. Boletín de SACCOM, 5(3), 15–25.
Honing, H. (2013b). Structure and Interpretation of Rhythm in Music. In The Psychology of Music (pp. 369–404). Elsevier.
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10.1016/b978-0-12-381460-9.00009-2
Honing, H. (2013c). Music Cognition Group.
Jaschke, A. C., Eggermont, L. H. P., Honing, H., & Scherder, E. J. A. (2013). Music education and its effect on intellectual abilities in children: a systematic review. Reviews in the Neurosciences, 24(6).
DOI
10.1515/revneuro-2013-0023
Sadakata, M., & McQueen, J. M. (2013). High stimulus variability in nonnative speech learning supports formation of abstract categories: Evidence from Japanese geminates. The Journal of the Acoustical Society of America, 134(2), 1324–1335.
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10.1121/1.4812767
Thompson-Schill, S., Hagoort, P., Dominey, P. F., Honing, H., Koelsch, S., Ladd, D. R., Lerdahl, F., Levinson, S. C., & Steedman, M. (2013). Multiple Levels of Structure in Language and Music. In Language, Music, and the Brain (pp. 289–304). The MIT Press.
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Van Balen, J., Burgoyne, J. A., Wiering, F., & Veltkamp, R. C. (2013). An Analysis of Chorus Features in Popular Song. In A. de Souza Britto Jr., F. Gouyon, & S. Dixon (Eds.), Proceedings of the 14th International Society for Music Information Retrieval Conference (pp. 107–112). ISMIR.
Vigliensoni, G., Burgoyne, J. A., & Fujinaga, I. (2013). MusicBrainz for the World: The Chilean Experience. In A. de Souza Britto Jr., F. Gouyon, & S. Dixon (Eds.), Proceedings of the 14th International Society for Music Information Retrieval Conference (pp. 131–136). ISMIR.
2012
Bouwer, F., & Honing, H. (2012). Rhythmic regularity revisited: Is beat induction indeed pre-attentive? In E. Cambouropoulos, C. Tsougras, P. Mavromatis, & K. Pastiadis (Eds.), Proceedings of the 12th International Conference on Music Perception and Cognition and 8th Triennial Conference of the European Society for the Cognitive Sciences of Music (pp. 122–127). Aristotle University of Thessaloniki.
Collier, D., Honing, H., & Oliver, R. (2012). REVIEWS. Journal of Music, Technology & Education, 5(1), 109–121.
DOI
10.1386/jmte.5.1.109_5
de Haas, W. B., & Burgoyne, J. A. (2012). Parsing the Billboard Chord Transcriptions (WorkingPaper No. 2012–18; UU-CS). Utrecht university.
Háden, G. P., Honing, H., & Winkler, I. (2012). Newborn infants are sensitive to sound timing. In F. Cambouropoulos, C. Tsougras, P. Mavromatis, & K. Pastiadis (Eds.), Proceedings of the 12th International Conference on Music Perception and Cognition and 8th Triennial Conference of the European Society for the Cognitive Sciences of Music (pp. 378–379). Aristotle University of Thessaloniki.
Hankinson, A., Burgoyne, J. A., Vigliensoni, G., & Fujinaga, I. (2012). Creating a large-scale searchable digital collection from printed music materials. Proceedings of the 21st International Conference on World Wide Web, 903–908.
DOI
10.1145/2187980.2188221
Hankinson, A., Porter, A., Burgoyne, J. A., Thompson, J., Vigliensoni, G., Liu, W., Chiu, R., & Fujinaga, I. (2012). Digital document image retrieval using optical music recognition. Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012, 577–582.
Honing, H. (2012a). Een vertelling. In S. van Maas, C. Hulshof, & P. Oldenhave (Eds.), Liber plurium vocum voor Rokus de Groot (pp. 150–154). Universiteit van Amsterdam.
Honing, H. (2012b). Iedereen is muzikaal. Wat we weten over het luisteren naar muziek (5e druk, uitgebreide editie). Nieuw Amsterdam Uitgevers.
Honing, H. (2012c). Op zoek naar wat ons muzikale dieren maakt. Nieuw Amsterdam Uitgevers.
Honing, H. (2012d). Without it no music: beat induction as a fundamental musical trait. Annals of the New York Academy of Sciences, 1252(1), 85–91. Portico.
DOI
10.1111/j.1749-6632.2011.06402.x
Honing, H., Merchant, H., Háden, G. P., Prado, L., & Bartolo, R. (2012a). Rhesus Monkeys (Macaca mulatta) Detect Rhythmic Groups in Music, but Not the Beat. PLoS ONE, 7(12), e51369.
DOI
10.1371/journal.pone.0051369
Honing, H., Merchant, H., Háden, G., Prado, L., & Bartolo, R. (2012b). Probing Beat Induction in Rhesus Monkeys: Is Beat Induction Species-Specific? In E. Cambouropoulos, C. Tsougras, P. Mavromatis, & K. Pastiadis (Eds.), Proceedings of the 12th International Conference on Music Perception and Cognition and 8th Triennial Conference of the European Society for the Cognitive Sciences of Music (pp. 454–455). Aristotle University of Thessaloniki.
Honing, H., & Ploeger, A. (2012). Cognition and the Evolution of Music: Pitfalls and Prospects. Topics in Cognitive Science, 4(4), 513–524. Portico.
DOI
10.1111/j.1756-8765.2012.01210.x
2011
Burgoyne, J. A., Wild, J., & Fujinaga, I. (2011). An expert ground-truth set for audio chord recognition and music analysis. Proceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011, 633–638.
Honing, H. (2011a). Muziek is geen luxe ... maar wat dan wel?: [Bespreking van: P. Ball (2010) The music instinct: How music works and why we can’t do without it]. De Academische Boekengids, 88, 2–4.
Honing, H. (2011b). The Illiterate Listener: On Music Cognition, Musicality and Methodology. Amsterdam University Press.
DOI
10.26530/oapen_480090
Honing, H. (2011c). We zijn het enige dier met maatgevoel. Parool.
Honing, H. (2011d). De mensen zijn muzikaal, de dieren niet. Friesch Dagblad.
Honing, H., & Bouwer, F. (2011, July). Is hierarchy in rhythm perception consciously learned?
Honing, H., & Romeijn, J. W. (2011). Surprise! Assessing the value of risky predictions. Proceedings of the Thirteenth International Conference on Informatics and Semiotics in Organisations - Problems and Possibilities of Computational Humanities (, 185.
Honing, H., Scherder, E. J. A., & Swaab, D. (2011). Amuzikaal zijn is de grote uitzondering. Volkskrant, Opinie & Debat.
Sadakata, M., & Sekiyama, K. (2011). Enhanced perception of various linguistic features by musicians: A cross-linguistic study. Acta Psychologica, 138(1), 1–10.
DOI
10.1016/j.actpsy.2011.03.007
Schaefer, R. S., Farquhar, J., Blokland, Y., Sadakata, M., & Desain, P. (2011). Name that tune: Decoding music from the listening brain. NeuroImage, 56(2), 843–849.
DOI
10.1016/j.neuroimage.2010.05.084
Smith, J. B. L., Burgoyne, J. A., Fujinaga, I., De Roure, D., & Downie, J. S. (2011). Design and creation of a large-scale database of structural annotations. Proceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011, 555–560.
Vigliensoni, G., Burgoyne, J. A., Hankinson, A., & Fujinaga, I. (2011). Automatic pitch recognition in printed square-note notation. Proceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011, 423–428.
2010
Brandmeyer, A., Timmers, R., Sadakata, M., & Desain, P. (2010). Learning expressive percussion performance under different visual feedback conditions. Psychological Research, 75(2), 107–121.
DOI
10.1007/s00426-010-0291-6
Computational Humanities Programme Committee, Willekens, F., Beaulieu, A., Bod, R., van den Bosch, A., & Honing, H. (2010). Computational Humanities: Computational Humanities Programme Committee, Royal Netherlands Academy of Arts and Science (KNAW). Royal Netherlands Academy of Arts.
Honing, H. (2010a). Beat-induction as a fundamental musical skill. In S. M. Demorest, S. J. Morrison, & P. S. Campbell (Eds.), Proceedings of the 11th International Conference on Music Perception and Cognition (p. 14). University of Washington.
Honing, H. (2010b). De ongeletterde luisteraar : Over muziekcognitie, muzikaliteit en methodologie. Amsterdam University Press.
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10.5117/9789056296605
Honing, H. (2010c). Iedereen is muzikaal (YouTube Channel bij boek). University of Amsterdam.
Honing, H. (2010d). Lure(d) into listening: The potential of cognition-based music information retrieval. Empirical Musicology Review, 5(4), 121–126.
Honing, H. (2010e). Iedereen is muzikaal (demonstraties en luistertests bij boek).
Honing, H. (2010f). Music Matters | A blog on music cognition.
McKay, C., Burgoyne, J. A., Hockman, J., Smith, J. B. L., Vigliensoni, G., & Fujinaga, I. (2010). Evaluating the genre classification performance of lyrical features relative to audio, symbolic and cultural features. Proceedings of the 11th International Society for Music Information Retrieval Conference, ISMIR 2010, 213–218.
2009
Burgoyne, J. A., Devaney, J., Ouyang, Y., Pugin, L., Himmelman, T., & Fujinaga, I. (2009). Lyric extraction and recognition on digital images of early music sources. Proceedings of the 10th International Society for Music Information Retrieval Conference, ISMIR 2009, 723–727.
Coath, M., Denham, S. L., Smith, L. M., Honing, H., Hazan, A., Holonowicz, P., & Purwins, H. (2009). Model cortical responses for the detection of perceptual onsets and beat tracking in singing. Connection Science, 21(2–3), 193–205.
DOI
10.1080/09540090902733905
Honing, H., & Ladinig, O. (2009). Exposure influences expressive timing judgments in music. Journal of Experimental Psychology: Human Perception and Performance, 35(1), 281–288.
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10.1037/a0012732
Honing, H., Ladinig, O., Háden, G. P., & Winkler, I. (2009a). Do newborn infants sense the beat? 200–201.
Honing, H., Ladinig, O., Háden, G. P., & Winkler, I. (2009b). Is Beat Induction Innate or Learned? Annals of the New York Academy of Sciences, 1169(1), 93–96. Portico.
DOI
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Ladinig, O., Honing, H., Háden, G., & Winkler, I. (2009). Probing Attentive and Preattentive Emergent Meter in Adult Listeners without Extensive Music Training. Music Perception, 26(4), 377–386.
DOI
10.1525/mp.2009.26.4.377
McKay, C., Burgoyne, J. A., Thompson, J., & Fujinaga, I. (2009). Using ace XML 2.0 to store and share feature, instance and class data for musical classification. Proceedings of the 10th International Society for Music Information Retrieval Conference, ISMIR 2009, 303–308.
Ouyang, Y., Burgoyne, J. A., Pugin, L., & Fujinaga, I. (2009). A robust border detection algorithm with application to medieval music manuscripts. Proceedings of the 2009 International Computer Music Conference, ICMC 2009, 101–104.
Rohrmeier, M., Rebuschat, P., Honing, H., Loui, P., Wiggins, G., Pearce, M. T., & Müllensiefen, D. (2009). Music cognition: Learning and processing. In N. A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 41–42). Cognitive Science Society.
Thompson, J., McKay, C., Burgoyne, J. A., & Fujinaga, I. (2009). Additions and improvements to the ace 2.0 music classifier. Proceedings of the 10th International Society for Music Information Retrieval Conference, ISMIR 2009, 435–440.
Winkler, I., Háden, G. P., Ladinig, O., Sziller, I., & Honing, H. (2009). Newborn infants detect the beat in music. Proceedings of the National Academy of Sciences, 106(7), 2468–2471.
DOI
10.1073/pnas.0809035106
2008
Burgoyne, J. A., Devaney, J., Pugin, L., & Fujinaga, I. (2008). Enhanced bleedthrough correction for early music documents with recto-verso registration. ISMIR 2008 - 9th International Conference on Music Information Retrieval, 407–412.
Honing, H. (2008a). De analfabetische luisteraar. In R. Diekstra & M. Hogenes (Eds.), Harmonie in gedrag: De maatschappelijke en pedagogische betekenis van muziek (pp. 29–35). Karakter.
Honing, H. (2008b). De vergeten luisteraar. Boekman, 20(77), 42–47.
Honing, H. (2008c). Musical competence and the role of exposure. 102.
Honing, H. (2008d). THE ROLE OF ICT IN MUSIC RESEARCH: A BRIDGE TOO FAR? International Journal of Humanities and Arts Computing, 1(1), 61–69.
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Honing, H., & de Haas, W. B. (2008). Swing Once More: Relating Timing and Tempo in Expert Jazz Drumming. Music Perception, 25(5), 471–476.
DOI
10.1525/mp.2008.25.5.471
Honing, H., & Ladinig, O. (2008). The Potential of the Internet for Music Perception Research: A Comment on Lab-Based Versus Web-Based Studies. Empirical Musicology Review, 3(1), 4–7.
DOI
10.18061/1811/31692
Honing, H., Ladinig, O., Winkler, I., & Háden, G. P. (2008). Probing emergent meter perception in adults and newborns using event-related brain potentials: a pilot study. 223.
Honing, H., & Reips, U.-D. (2008). Web-based versus Lab-based Studies:A Response to Kendall (2008). Empirical Musicology Review, 3(2), 73–77.
DOI
10.18061/1811/31943
Ladinig, O., & Honing, H. (2008). An empirically validated model of complexity: Longuet-Higgins and Lee reconsidered. 89.
Pugin, L., Hockman, J., Burgoyne, J. A., & Fujinaga, I. (2008). Gamera versus aruspix two optical music recognition approaches. ISMIR 2008 - 9th International Conference on Music Information Retrieval, 419–424.
Smith, L. M., & Honing, H. (2008a). A multiresolution model of rhythmic expectancy. In K. Miyazaki, Y. Hiraga, M. Adachi, Y. Nakajima, & M. Tsuzaki (Eds.), Proceedings of the 10th International Conference on Music Perception and Cognition (ICMPC 10), Sapporo, Japan (pp. 360–365). Hokkaido University.
Smith, L. M., & Honing, H. (2008b). Time–frequency representation of musical rhythm by continuous wavelets. Journal of Mathematics and Music, 2(2), 81–97.
DOI
10.1080/17459730802305336
2007
Burgoyne, J. A., & McAdams, S. (2007). Non-linear scaling techniques for uncovering the perceptual dimensions of timbre. 73–76.
Burgoyne, J. A., Pugin, L., Eustace, G., & Fujinaga, I. (2007). A comparative survey of image binarisation algorithms for optical recognition on degraded musical sources. Proceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007, 509–512.
Burgoyne, J. A., Pugin, L., Kereliuk, C., & Fujinaga, I. (2007). A cross-validated study of modelling strategies for automatic chord recognition in audio. Proceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007, 251–254.
Coath, M., Denham, S. L., Smith, L. M., Honing, H., Hazan, A., & Purwins, H. (2007). An auditory model for the detection of perceptual onsets and beat tracking in singing. In H. P. D.R. Hardoon (Ed.), Workshop at Neural Information Processing Systems (NIPS) conference. NIPS.
Honing, H. (2007a). Noten of letters: de taal van de muziek en het plezier van het luisteren. De Academische Boekengids, 63, 6–7.
Honing, H. (2007b). Preferring the best fitting, least flexible, and most surprising prediction: Towards a Bayesian approach to model selection in music cognition. Proceedings of the Society for Music Perception and Cognition (SMPC), 37.
Honing, H. (2007c). Is expressive timing relational invariant under tempo transformation? Psychology of Music, 35(2), 276–285.
DOI
10.1177/0305735607070380
Ladinig, O., & Honing, H. (2007). Complexity judgments as a measure for metric salience: Is there indeed a difference between musicians and non-musicians? Proceedings of the Society for Music Perception and Cognition (SMPC), 27.
Pugin, L., Burgoyne, J. A., & Fujinaga, I. (2007a). Map adaptation to improve optical music recognition of early music documents using hidden markov models. Proceedings of the 8th International Conference on Music Information Retrieval, ISMIR 2007, 513–516.
Pugin, L., Burgoyne, J. A., & Fujinaga, I. (2007b). Goal-directed evaluation for the improvement of optical music recognition on early music prints. Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries, 303–304.
DOI
10.1145/1255175.1255233
Smith, L. M., & Honing, H. (2007). Evaluation of multiresolution representations of musical rhythm. In E. Schubert, K. Buckley, R. Eliott, B. Koboroff, J. Chen, & C. Stevens (Eds.), Proceedings of the International Conference on Music Communication Science. MARCS.
2006
Honing, H. (2006a). Evidence for tempo-specific timing in music using a web-based experimental setup. Journal of Experimental Psychology: Human Perception and Performance, 32(3), 780–786.
DOI
10.1037/0096-1523.32.3.780
Honing, H. (2006b). How to make a machine listen? Intensive Science (Sony Computer Science Laboratoy), 21.
Honing, H. (2006c). Music and Cognition: What cognitive science can learn from music cognition. Proceedings of the Annual Conference of the Cognitive Science Society, 2655.
Honing, H. (2006d). On the growing role of observation, formalization and experimental method in musicology. Empirical Musicology Review, 1(1), 2–5.
Honing, H. (2006e). The role of surprise in theory testing: Some preliminary observations. Proceedings of the International Conference on Music Perception and Cognition, 38–42.
Honing, H. (2006f). Computational Modeling of Music Cognition: A Case Study on Model Selection. Music Perception, 23(5), 365–376.
DOI
10.1525/mp.2006.23.5.365
Honing, H., & Ladinig, O. (2006). The effect of exposure and expertise on timing judgments: Preliminary results. Proceedings of the International Conference on Music Perception and Cognition, 80–85.
Li, B., Burgoyne, J. A., & Fujinaga, I. (2006). Extending Audacity for audio annotation. ISMIR 2006 - 7th International Conference on Music Information Retrieval, 379–380.
Sadakata, M., Desain, P., & Honing, H. (2006). The Bayesian Way to Relate Rhythm Perception and Production. Music Perception, 23(3), 269–288.
DOI
10.1525/mp.2006.23.3.269
Smith, L. M., & Honing, H. (2006). Evaluating and extending computational models of rhythmic syncopation in music. International Computer Music Conference, ICMC 2006, 688–691.
2005
Burgoyne, J. A., & Saul, L. K. (2005a). Learning harmonic relationships in digital audio with dirichlet-based hidden Markov models. ISMIR 2005 - 6th International Conference on Music Information Retrieval, 438–443.
Burgoyne, J. A., & Saul, L. K. (2005b). Visualization of low dimensional structure in Tonal Pitch Space.
Honing, H. (2005a). Music cognition: Theory testing and model selection. Proceedings of the Annual Conference of the Cognitive Science Society, 38–38.
Honing, H. (2005b). Timing is tempo-specific. International Computer Music Conference, ICMC 2005.
Honing, H. (2005c). Muziek is geen geluid: Over muziek, kunst en wetenschap. BLIND : Interdisciplinair Tijdschrift, 4.
HONING, H. (2005). I<scp>S</scp> T<scp>HERE A</scp> P<scp>ERCEPTION</scp>-B<scp>ASED</scp> A<scp>LTERNATIVE TO</scp> K<scp>INEMATIC</scp> M<scp>ODELS OF</scp> TEMPO RUBATO? Music Perception, 23(1), 79–85.
DOI
10.1525/mp.2005.23.1.79
Jongsma, M. L. A., Eichele, T., Quiroga, R. Q., Jenks, K. M., Desain, P., Honing, H., & Van Rijn, C. M. (2005). Expectancy effects on omission evoked potentials in musicians and non‐musicians. Psychophysiology, 42(2), 191–201. Portico.
DOI
10.1111/j.1469-8986.2005.00269.x
2004
Honing, H. (2004a). Een vertelling over muziek, motoriek en metafoor. Mens & Melodie, 59(5), 5–9.
Honing, H. (2004b). Is there a perception-based alternative to kinematic models of tempo rubato? (WorkingPaper PP-2004-17; Technical Reports). Institute for Logic, Language.
Honing, H. (2004c). Is Timing Tempo-Specific? An Online Internet Experiment on Perceptual Invariance of Timing in Music (WorkingPaper PP-2004-34; Technical Reports). Institute for Logic, Language.
Honing, H. (2004d). Je weet niet wat je hoort: wiskunde en muziekcognitie. Nieuw Archief voor Wiskunde, 5/5(3), 228–231.
Honing, H. (2004e). Muziek de maat genomen. Over de groeiende rol van theorie en observatie in de musicologie. De Academische Boekengids, 4(7), 23–23.
Honing, H. (2004f). The comeback of systematic musicology: new empiricism and the cognitive revolution. Dutch Journal of Music Theory, 9(3), 241–244.
Honing, H. (2004g). When a good fit is not good enough: a case study on the final ritard. In Ashley, R & Lipscomb, S. (Eds.), Proceedings of the International Conference on Music Perception and Cognition (ICMPC) (pp. 510–513). Northwestern University.
Honing, H. (2004h). Wiskunde en muziekcognitie (WorkingPaper PP-2004-09; Technical Reports). Institute for Logic, Language.
Honing, H. (2004i). Het geheim van de syncope. Over muziekcognitie, meten aan uitvoeringen, spannende ritmes, en de aandacht van baby’s. De Groene Amsterdammer 45, 28–29.
Honing, H., Desain, P., & Sadakata, M. (2004). An analysis of rhythmic ratios in scores of various kinds of music. In Ashley, R & Lipscomb, S. (Eds.), Proceedings of the International Conference on Music Perception and Cognition (ICMPC). Northwestern University.
Jongsma, M. L. A., Desain, P., & Honing, H. (2004). Rhythmic context influences the auditory evoked potentials of musicians and nonmusicians. Biological Psychology, 66(2), 129–152.
DOI
10.1016/j.biopsycho.2003.10.002
Sadakata, M., Desain, P., Honing, H., Patel, A., & Iversen, J. R. (2004). A cross-cultural study of the rhythm in English and Japanese popular music. Proceedings of the International Symposium on Musical Acoustics, 41–44.
Sha, F., Burgoyne, J. A., & Saul, L. K. (2004). Multiband statistical learning for F 0 estimation in speech. Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, 5, V-661-V–664.
2003
Desain, P., & Honing, H. (2003a). Single trial ERP allows Detection of Perceived and Imagined Rhythm. In K. Hirata (Ed.), Proceedings of the RENCON workshop, International Joint Conference on Artificial Intelligence (IJCAI) (pp. 1–4). NTT Communication Science Laboratories.
Desain, P., & Honing, H. (2003b). The Formation of Rhythmic Categories and Metric Priming. Perception, 32(3), 341–365.
DOI
10.1068/p3370
Honing, H. (2003a). Some comments on the relation between music and motion. Music Theory Online, 9(1).
Honing, H. (2003b). The Final Ritard: On Music, Motion, and Kinematic Models. Computer Music Journal, 27(3), 66–72.
DOI
10.1162/014892603322482538
Honing, H., & Desain, P. (2003). Final Report NWO-PIONIER Project “Music, Mind, Machine.” ILLC, University of Amsterdam.
Honing, H., Desain, P., & Timmers, R. (2003). Music Performance Panel: NICI / MMM Position Statement. Proceedings of the MOSART Midterm Meeting, 318–322.
Honing, H., Patel, A., Sadakata, M., Desain, P., & Iversen, J. R. (2003). An analysis of rhythm in japanese and english popular music. In T. Taguti, et al. (Ed.), Proceedings of the Annual meeting of the Japanese Society for Music Perception and Cognition (pp. 1–4). International Symposium on Musiacl Acoustics.
JONGSMA, M. L. A., DESAIN, P., HONING, H., & VAN RIJN, C. M. (2003). Evoked Potentials to Test Rhythm Perception Theories. Annals of the New York Academy of Sciences, 999(1), 180–183. Portico.
DOI
10.1196/annals.1284.025
van Zaanen, M. M., Bod, R., & Honing, H. (2003). A memory-based approach to meter induction. Proceedings of the ESCOM, 250–253.
2002
Desain, P., & Honing, H. (2002). Rhythmic stability as explanation of category size. In K. Stevens (Ed.), Proceedings of the International Conference on Music Perception and Cognition (pp. 111–115). University of New South Wales.
Honing, H., Sadakata, H. M., & Desain, P. (2002). The relation between rhythm perception and production: towards a bayesian model. In K. Ogushi (Ed.), Proceedings of the Japanese Society of Music Perception and Cogntion (pp. 123–127).
Honing, H., van Rijn, T., Coenen, T., Jenks, K., & Desain, P. (2002). Omission evoked potentials (OEPS) in rhythmically trained and non-trained subjects. Journal of Cognitive Neuroscience, B90.
Honing, H., van Rijn, T., Jongsma, M. A., & Desain, P. (2002). Aep p300 modulation by two different temporal contexts in both rhythmically trained and nontrained subjects. Journal of Cognitive Neuroscience, A94.
Timmers, R., Ashley, R., Desain, P., Honing, H., & Windsor, W. L. (2002). Timing of Ornaments in the Theme from Beethoven’s Paisiello Variations: Empirical Data and a Model. Music Perception, 20(1), 3–33.
DOI
10.1525/mp.2002.20.1.3
Timmers, R., & Honing, H. (2002). On music performance, theories, measurement and diversity. Cognitive Processing (International Quarterly of Cognitive Sciences), 1/2, 1–19.
2001
Honing, H. (2001). From Time to Time: The Representation of Timing and Tempo. Computer Music Journal, 25(3), 50–61.
DOI
10.1162/014892601753189538
Rossignol, S., Desain, P., & Honing, H. (2001a). Refined knowledge-based pitch tracking: Comparing Three Frequency Extraction Methods. Proceedings of the International Computer Music Conference, 2001.
Rossignol, S., Desain, P., & Honing, H. (2001b). State-of-the-art in fundamental frequency tracking. Proceedings of workshop on Current Research Directions in Computer Music, 244–245.
Trilsbeek, P., Desain, P., & Honing, H. (2001). Spectral Analysis of Timing Profiles of Piano Performances. Proceedings of the International Computer Music Conference, 2001.
2000
Cemgil, A. T., Kappen, B., Desain, P., & Honing, H. (2000). On tempo tracking: Tempogram Representation and Kalman filtering. Journal of New Music Research, 29(4), 259–273.
DOI
10.1080/09298210008565462
Desain, P., Jansen, C., & Honing, H. (2000). How identification of rhythmic categories depends on tempo and meter. Proceedings of the International Conference of Music perception and Cognition.
Heijink, H., Desain, P., Honing, H., & Windsor, L. (2000). Make Me a Match: An Evaluation of Different Approaches to Score—Performance Matching. Computer Music Journal, 24(1), 43–56.
DOI
10.1162/014892600559173
Timmers, R., Desain, P., & Honing, H. (2000). Timing of grace notes in piano performances of a Beethoven theme. Proceedings of the 8th Rhythm Perception and Production Workshop.
Windsor, W. L., Desain, P., Honing, H., Aarts, R., & Heijink, H. (2000). On time: the influence of tempo, structure and style on the timing of grace notes in skilled musical perfomance. In Desain, P. & Windsor, W. L. (Eds.), Rhythm perception and production (pp. 217–223). Swets & Zeitlinger.
1999
Desain, P., & Honing, H. (1999a). Modeling vibrato and portamento in music performance. Bulletin of the Council for Research in Music Education.
Desain, P., & Honing, H. (1999b). Computational Models of Beat Induction: The Rule-Based Approach. Journal of New Music Research, 28(1), 29–42.
DOI
10.1076/jnmr.28.1.29.3123
1998
Desain, P., & Honing, H. (1998). A reply to S. W. Smoliar’s “Modelling musical perception: a critical view.” In Griffith, N. & Todd, P. (Eds.), Musical networks, parallel distributed perception and performance (pp. 111–114). MIT Press.
Desain, P., Honing, H., Aarts, R., & Timmers, R. (1998). Rhythmic aspects of vibrato. Proceedings of the 1998 rhythm Perception and Production Workshop, 34–34.
Desain, P., Honing, H., Vanthienen, H., & Windsor, L. (1998). Computational Modeling of Music Cognition: Problem or Solution? Music Perception, 16(1), 151–166.
DOI
10.2307/40285783
Honing, H. (1998). Vergelijking MIDI-files: deskundige rapport (rechtzaak Utrecht). Universiteit van Amsterdam / Universiteit van Nijmegen.
1997
Desain, P., & Honing, H. (1997a). How to evaluate generative models of expression in music performance. IJCAI workshop: Issues in AI and music evaluation and assessment, 5–7.
Desain, P., & Honing, H. (1997b). Music, Mind, Machine: beatinductie computationeel modelleren. Informatie, 39, 48–53.
Desain, P., & Honing, H. (1997c). Structural Expression Component Theory (SECT), and a method for decomposing expression in music performance. Proceedings of the Society for Music Perception and Cognition, 38–38.
Desain, P., & Honing, H. (1997d). CLOSe to the edge? Advanced object‐oriented techniques in the representation of musical knowledge*. Journal of New Music Research, 26(1), 1–16.
DOI
10.1080/09298219708570714
Desain, P., & Honing, H. (1997e). Lisp as a second language.
Desain, P., Honing, H., & Heijink, H. (1997). Robust score-performance matching: taking advantage of structural information. Proceedings of the International Computer Music Conference, 1997, 337–340.
Windsor, W. L., Desain, P., Honing, H., Aarts, R., & Heijink, H. (1997). Graceful timing: ornaments, tempo and musical structure. Proceedings of the 7t Rhythm Perception and Production Workshop, 35–35.
1996
Desain, P., & Honing, H. (1996a). Mentalist and physicalist models of expressive timing. In Abstracts of the 1996 Rhythm Perception and Production Workshop (p. 14). Max Planck-Institute.
Desain, P., & Honing, H. (1996b). Modeling Continuous Aspects of Music Performance: Vibrato and Portamento. In Proceedings of the 4th International Music Perception and Cognition Conference. McGill University.
Desain, P., & Honing, H. (1996c). Pas op voor de tempocurve! [Beware of the Tempo Curve]. Nieuwsbrief Nederlandse Vereniging voor Psychonomie, 1, 4–7.
Desain, P., & Honing, H. (1996d). Physical motion as a metaphor for timing in music: the final ritard. Proceedings of the International Computer Music Conference, 1996, 458–460.
1995
Dannenberg, R. B. (1995). Review: Music, Mind and Machine: Studies in Computer Music, Music Cognition and Artificial Intelligence, by Peter Desain and Henkjan Honing. Music Perception, 12(3), 365–367.
DOI
10.2307/40286189
Honing, H. (1995). The Vibrato Problem: Comparing Two Solutions. Computer Music Journal, 19(3), 32.
DOI
10.2307/3680653
Honing, H., & Desain, P. (1995a). Computationeel modelleren van beat-inductie. In Van frictie tot wetenschap. Jaarboek 1994-1995 (pp. 83–95). Vereniging van Academie-onderzoekers.
Honing, H., & Desain, P. (1995b). Towards algorithmic descriptions for continuous modulations of musical parameters. Proceedings of the International Computer Music Conference, 1995, 393–395.
Kappert, P., Desain, P., & Honing, H. (1995). Expresso: het retoucheren (en analyseren) van pianouitvoeringen. Abstracts vijfde congres Nederlandse Vereniging voor Psychonomie, 20–21.
Vantomme, J. D., Desain, P., & Honing, H. (1995). Music, Mind and Machine: Studies in Computer Music, Music Cognition and Artificial Intelligence. Computer Music Journal, 19(2), 107.
DOI
10.2307/3680605
1994
Desain, P., & Honing, H. (1994a). Rule-based models of initial beat induction and an analysis of their behaviour. Proceedings of the International Computer Music Conference, 20, 80–82.
Desain, P., & Honing, H. (1994b). Does expressive timing in music performance scale proportionally with tempo? Psychological Research, 56(4), 285–292.
DOI
10.1007/bf00419658
Honing, H., & Desain, P. (1994a). Advanced issues in beat induction modeling: syncopation, tempo and timing. Proceedings of the International Computer Music Conference, 20, 92–94.
Honing, H., & Desain, P. (1994b). Can music cognition benefit from computer music research? From foot-tapper systems to beat induction models. Proceedings of the ICMPC 1994, 3, 397–398.
Honing, H., & Desain, P. (1994c). Foot-tapping: a brief introduction to beat induction. Proceedings of the International Computer Music Conference, 20, 78–79.
1993
Desain, P., & Honing, H. (1993a). On continuous musical control of discrete musical objects. Proceedings of the International Computer Music Conference, 1993, 218–221.
Desain, P., & Honing, H. (1993b). Tempo curves considered harmful. Contemporary Music Review, 7(2), 123–138.
DOI
10.1080/07494469300640081
Honing, H. (1993a). A microworld approach to the formalization of musical knowledge. Computers and the Humanities, 27(1), 41–47.
DOI
10.1007/bf01830716
Honing, H. (1993b). Issues on the representation of time and structure in music. Contemporary Music Review, 9(1–2), 221–238.
DOI
10.1080/07494469300640461
Honing, H., & Rocchesso, D. (1993). International Workshop on Models and Representations of Musical Signals, Capri, Italy, October 1992. Computer Music Journal, 17(2), 80.
DOI
10.2307/3680872
Rowe, R., Garton, B., Desain, P., Honing, H., Dannenberg, R., Jacobs, D., Pope, S. T., Puckette, M., Lippe, C., Settel, Z., & Lewis, G. (1993). Editor’s Notes: Putting Max in Perspective. Computer Music Journal, 17(2), 3.
DOI
10.2307/3680864
1992
Dannenberg, R. B., Desain, P., & Honing, H. (1992). Time Functions. Computer Music Journal, 16(3), 7.
DOI
10.2307/3680844
Desain, P., & Honing, H. (1992). Time Functions Function Best as Functions of Multiple Times. Computer Music Journal, 16(2), 17.
DOI
10.2307/3680713
Honing, H. (1992). EXPRESSO, A STRONG AND SMALL EDITOR FOR EXPRESSION. Proceedings of the International Computer Music Conference, 1992, 215–218.
1991
Desain, P., & Honing, H. (1991). Generalized Time Functions. Proceedings of the International Computer Music Conference, 17, 348–351.
1990
Honing, H. (1990). POCO: AN ENVIRONMENT FOR ANALYSING, MODIFYING, AND GENERATING EXPRESSION IN MUSIC. Proceedings of the International Computer Music Conference, 16, 364–368.
1989
Desain, P., & Honing, H. (1989a). Report on the First AIM Conference Sankt Augustin, Germany September 1988. Perspectives of New Music, 27(2), 282.
DOI
10.2307/833418
Desain, P., & Honing, H. (1989b). The Quantization of Musical Time: A Connectionist Approach. Computer Music Journal, 13(3), 56.
DOI
10.2307/3680012
Desain, P., Honing, H., & De Rijk, K. (1989). A CONNECTIONIST QUANTIZER. Proceedings of the International Computer Music Conference, 15, 80–85.
1988
Desain, P., & Honing, H. (1988). LOCO: A Composition Microworld in Logo. Computer Music Journal, 12(3), 30.
DOI
10.2307/3680334
1986
Desain, P., & Honing, H. (1986). LOCO: Composition Microworlds in LOGO. Proceedings of the International Computer Music Conference, 12, 109–118.
Without date
Burgoyne, J. A., & McAdams, S. (n.d.). A Meta-analysis of Timbre Perception Using Nonlinear Extensions to CLASCAL. In Lecture Notes in Computer Science (pp. 181–202). Springer Berlin Heidelberg.
DOI
10.1007/978-3-540-85035-9_12
It Turns Out We Were Born To Groove. (n.d.).
Pugin, L., Burgoyne, J. A., & Fujinaga, I. (n.d.). Reducing Costs for Digitising Early Music with Dynamic Adaptation. In Lecture Notes in Computer Science (pp. 471–474). Springer Berlin Heidelberg.
DOI
10.1007/978-3-540-74851-9_45
The e-proceedings of the 17th International Conference on Music Perception and Cognition and the 7th Conference of the Asia-Pacific Society for the Cognitive Sciences of Music. (n.d.).
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