Publications

Export 54 results:
Author Title Type [ Year(Asc)]
2022
Agres KR, Tay TYuan, Pearce M.  2022.  Comparing Musicians and Non-musicians’ Expectations in Music and Vision. ACM Audio Mostly. :1-8. (369.23 KB)
Chua P, Gupta C, Agres KR, Nanayakkara S.  2022.  Computational Music Systems for Emotional Health and Wellbeing: A Review. ACM Special Interest Group on Computer–Human Interaction (SIGHCI) 2022.  (347.85 KB)
Agres KR, Ureyang N.  2022.  Engaging deeply with cognitive science in a conservatory of music: Using student-centered learning to enhance learning outcomes in music students. Proceedings of the 35th conference for the International Society of Music Education (ISME 2022). :1-15. (266.29 KB)
Agres KR, Ureyang N.  2022.  Improving Students’ Practice and Performance of Music by Incorporating Cognitive Science into Conservatory Curricula. Proceedings of the 35th conference for the International Society of Music Education (ISME 2022). :1-13. (258.63 KB)
2020
Herff SA, Zhen S, Yu R, Agres KR.  2020.  Age dependent statistical learning trajectories reveal differences in information weighting. Psychology and Aging.  (1.79 MB)
Nahar F, Agres K, Balamurali B, Herremans D.  2020.  A dataset and classification model for Malay, Hindi, Tamil and Chinese music. Workshop on Machine Learning and Music (MML 2020), at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) conference.
Agres KR.  2020.  Developing Music Technology for Emotion Regulation and Motor Rehabilitation. Proceedings of the 16th WFMT World Congress of Music Therapy.  (67.56 KB)
Cheuk K.W., Agres K., Herremans D..  2020.  The impact of Audio input representations on neural network based music transcription. Proceedings of the International Joint Conference on Neural Networks (IJCNN).  (1.87 MB)
Cheuk KWai, Anderson H, Agres K, Herremans D.  2020.  nnAudio:  An on-the-fly GPU Audio toSpectrogram Conversion Toolbox Using 1D Convolutional Neural Networks. IEEE Access. 8:161981-162003. (6.65 MB)
Luo Y-J, Hsu C-C, Agres K, Herremans D.  2020.  Singing Voice Conversion with Disentangled Representations of Singer and Vocal Technique Using Variational Autoencoders. 45th International Conference on Acoustics, Speech, and Signal Processing (IEEE ICASSP 2020).  (2.88 MB)
2019
Agres K.  2019.  Change detection and schematic processing in music. Psychology of Music. 47(2):173-193.
Ehrlich S, Agres K, Guan C, Cheng G.  2019.  A closed-loop, music-based brain-computer interface for emotion mediation. PLoS ONE. 14(3):e0213516. (1.76 MB)
Bilgin P, Agres K, Robinson N, Wai AAung Phyo, Guan C.  2019.  A Comparative Study of Mental States in 2D and 3D Virtual Environments Using EEG. IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC).  (812.97 KB)
Agres K, Bigo L, Herremans D.  2019.  The impact of musical structure on enjoyment and absorptive listening states in trance music. Music and Consciousness 2: Worlds, Practices, Modalities. Edited by Ruth Herbert, David Clarke, and Eric Clarke
Luo Y.J., Agres K., Herremans D..  2019.  Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders. ISMIR.  (5.62 MB)
Cheuk K.W., Agres K., Herremans D..  2019.  nnAudio: A PyTorch Audio Processing Tool Using 1D Convolution neural networks. ISMIR - Late Breaking Demo.  (399.08 KB)
Agres K, Lui S, Herremans D.  2019.  A novel music-based game with motion capture to support cognitive and motor function in the elderly. IEEE Conference on Games (CoG) 2019.  (2.63 MB)
McGregor S, Agres K, Rataj K, Purver M, Wiggins G.  2019.  Re-Representing Metaphor: Modeling Metaphor Perception Using Dynamically Contextual Distributional Semantics. Frontiers in Psychology: Cognitive Science. 10(765):1-18. (2.11 MB)
Herff S, Rashid N.A, Lee J, Lee T.S, Agres K.  2019.  Statistical Learning Ability as a Measure of Cognitive Function. :1-7. (1004.22 KB)
2018
Chuan C-H, Agres K, Herremans D.  2018.  From Context to Concept: Exploring Semantic Relationships in Music with Word2Vec. Neural Computing and Applications. https://doi.org/10.1007/s00521-018-3923-1 (1.64 MB)
Agres K, Abdallah S, Pearce M.  2018.  Information-Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory. Cognitive Science. 42:43-76. (410.27 KB)
Agres K, Meredith D.  2018.  Modelling Novice and Expert Listeners’ Ability to Detect Changes in Short Melodies. International Conference on Music Perception and Cognition.  (93.32 KB)
Beveridge S., Cano E., Agres K..  2018.  Rhythmic Entrainment for Hand Rehabilitation Using the Leap Motion Controller. Proceedings of The 19th International Society of Music Information Retrieval (ISMIR) Conference.  (476.62 KB)
Agres K, Herremans D.  2018.  The Structure of Chord Progressions Influences Listeners’ Enjoyment and Absorptive States in EDM. International Conference on Music Perception and Cognition.  (387.15 KB)
2017
Cancino-Chacon C, Grachten M, Agres K.  2017.  From Bach to the Beatles: The simulation of human tonal expectation using ecologically-trained predictive models. International Society for Music Information Retrieval Conference (ISMIR).  (298.14 KB)
Agres K, Herremans D, Bigo L, Conklin D.  2017.  Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music. Frontiers in Psychology. 7:1999. (1.15 MB)
Ibrahim K, Grunberg D, Agres K, Gupta C, Wang Y.  2017.  Intelligibility of Sung Lyrics: A Pilot Study. International Society for Music Information Retrieval Conference (ISMIR).  (288.5 KB)
Agres K, Herremans D.  2017.  Music and Motion-Detection: A Game Prototype for Rehabilitation and Strengthening in the Elderly. IEEE International Conference on Orange Technologies (ICOT 2017).  (1.77 MB)
2016
Agres K., Bigo L., Herremans D., Conklin D..  2016.  The Effect of Repetitive Structure on Enjoyment in Uplifting Trance Music. In Proceedings of the 14th International Conference for Music Perception and Cognition (ICMPC). :280-282. (139.27 KB)
Forth J, Agres K, Purver M, Wiggins G.  2016.  Entraining IDyOT: timing in the information dynamics of thinking. Frontiers in Psychology: Auditory Cognitive Neuroscience. 7:1575 (2.85 MB)
Agres K, Forth J, Wiggins GA.  2016.  Evaluation of Musical Creativity and Musical Metacreation Systems. ACM Comput. Entertain.. 14(3):3:1–3:33. (393.86 KB)
Wiggins GA, Agres K, Forth J, Purver M.  2016.  The Information Dynamics of Thinking: a cognitive architecture for human creative cognition.  (61.62 KB)
Xiao P, Alnajjar K, Granroth-Wilding M, Agres K, Toivonen H.  2016.  Meta4meaning: Automatic Metaphor Interpretation Using Corpus-Derived Word Associations. Proceedings of the Seventh International Conference on Computational Creativity.
Agres KR, McGregor S, Rataj K, Purver M, Wiggins GA.  2016.  Modeling metaphor perception with distributional semantics vector space models. Workshop on Computational Creativity, Concept Invention, and General Intelligence.  (295.07 KB)
Agres KR, Sauvé SA.  2016.  Workshop on Auditory Neuroscience, Cognition, and Modeling. Psychomusicology: Music, Mind, and Brain. 26(3):288-292.
2015
Agres K, McGregor S, Purver M, Wiggins G.  2015.  Conceptualizing Creativity: From Distributional Semantics to Conceptual Spaces. Proceedings of the Sixth International Conference on Computational Creativity.  (187.9 KB)
Agres K., Chacón C.ECancino, Grachten M., Lattner S..  2015.  Co-occurrences of harmonics bootstrap pitch and tonality perception in music: Evidence from a statistical unsupervised learning model. CogSci 2015: The annual meeting of the Cognitive Science Society.  (217.54 KB)
McGregor S, Agres K, Purver M, Wiggins GA.  2015.  From Distributional Semantics to Conceptual Spaces: A Novel Computational Method for Concept Creation. Journal of Artificial General Intelligence. 6(1):55-86. (289.07 KB)
Lattner S, Grachten M, Agres K, Chacón C.  2015.  Probabilistic Segmentation of Musical Sequences using Restricted Boltzmann Machines. Mathematics and Computation in Music. 9110:323-334. (111.94 KB)
Agres K, Wiggins GA.  2015.  Schematic processing as a framework for learning and creativity in CBR and CC. Proceedings of the 23rd International Conference on Case-Based Reasoning. :151-155. (112.03 KB)
2013
Agres K, Abdallah S, Pearce M.  2013.  An information-theoretic account of musical expectation and memory. Proceedings of the 35th Annual Conference of the Cognitive Science Society.  (422.99 KB)
Agres K.  2013.  The Learning Trajectory Of Musical Memory: From Schematic Processing Of Novel Melodies To Robust Musical Memory Representations. Cornell University, Department of Psychology. PhD
2009
Agres KR, DeLong JE, Spivey M.  2009.  The sparsity of simple recurrent networks in musical structure learning. Proceedings of the 31th Annual Conference of the Cognitive Science Society.  (591.97 KB)
2008
Agres KR, Krumhansl CL.  2008.  Musical change deafness: The inability to detect change in a non-speech auditory domain. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 969-974).  (352.36 KB)
Krumhansl CL, Agres KR.  2008.  Musical expectancy: The influence of musical structure on emotional response. Behavioral and Brain Sciences. 31(5):584–585.