Marcus T. Pearce

According to our database, Marcus T. Pearce authored at least 28 papers between 2004 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Modeling enculturated bias in entrainment to rhythmic patterns.

Thomas Kaplan, Jonathan Cannon, Lorenzo Jamone, Marcus T. Pearce

PLoS Comput. Biol., September, 2022

Comparing Musicians and Non-musicians' Expectations in Music and Vision.

Kat Agres, Ting Yuan Tay, Marcus T. Pearce

Proceedings of the AM '22: AudioMostly 2022, St. Pölten, 2022

2021

Correction: PPM-Decay: A computational model of auditory prediction with memory decay.

Peter M. C. Harrison, Roberta Bianco, Maria Chait, Marcus T. Pearce

PLoS Comput. Biol., 2021

2020

PPM-Decay: A computational model of auditory prediction with memory decay.

Peter M. C. Harrison, Roberta Bianco, Maria Chait, Marcus T. Pearce

PLoS Comput. Biol., November, 2020

Investigating the Perceptual Validity of Evaluation Metrics for Automatic Piano Music Transcription.

Adrien Ycart, Lele Liu, Emmanouil Benetos, Marcus T. Pearce

Trans. Int. Soc. Music. Inf. Retr., 2020

From learning to creativity: Identifying the behavioural and neural correlates of learning to predict human judgements of musical creativity.

Ioanna Zioga, Peter M. C. Harrison, Marcus T. Pearce, Joydeep Bhattacharya, Caroline Di Bernardi Luft

NeuroImage, 2020

Decomposing neural responses to melodic surprise in musicians and non-musicians: Evidence for a hierarchy of predictions in the auditory system.

David Ricardo Quiroga-Martinez, Niels Christian Hansen, Andreas Højlund Nielsen, Marcus T. Pearce, Elvira Brattico, Peter Vuust

NeuroImage, 2020

Auditory but Not Audiovisual Cues Lead to Higher Neural Sensitivity to the Statistical Regularities of an Unfamiliar Musical Style.

Ioanna Zioga, Peter M. C. Harrison, Marcus T. Pearce, Joydeep Bhattacharya, Caroline Di Bernardi Luft

J. Cogn. Neurosci., 2020

Musical Features for Automatic Music Transcription Evaluation.

Adrien Ycart, Lele Liu, Emmanouil Benetos, Marcus T. Pearce

CoRR, 2020

2019

Intracranial Recordings and Computational Modeling of Music Reveal the Time Course of Prediction Error Signaling in Frontal and Temporal Cortices.

Diana Omigie, Marcus T. Pearce, Katia Lehongre, Dominique Hasboun, Vincent Navarro, Claude Adam, Séverine Samson

J. Cogn. Neurosci., 2019

2018

Information-Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory.

Kat Agres, Samer Abdallah, Marcus T. Pearce

Cogn. Sci., 2018

An Energy-based Generative Sequence Model for Testing Sensory Theories of Western Harmony.

Peter M. C. Harrison, Marcus T. Pearce

Proceedings of the 19th International Society for Music Information Retrieval Conference, 2018

2015

A New Look at Musical Expectancy: The Veridical Versus the General in the Mental Organization of Music.

Emery Schubert, Marcus T. Pearce

Proceedings of the Music, Mind, and Embodiment - 11th International Symposium, 2015

2013

Do Online Social Tags Predict Perceived or Induced Emotional Responses to Music?

Yading Song, Simon Dixon, Marcus T. Pearce, Andrea R. Halpern

Proceedings of the 14th International Society for Music Information Retrieval Conference, 2013

A Distributed Model For Multiple-Viewpoint Melodic Prediction.

Srikanth Cherla, Tillman Weyde, Artur S. d'Avila Garcez, Marcus T. Pearce

Proceedings of the 14th International Society for Music Information Retrieval Conference, 2013

Harmonising Melodies: Why Do We Add the Bass Line First?

Raymond Whorley, Christophe Rhodes, Geraint A. Wiggins, Marcus T. Pearce

Proceedings of the Fourth International Conference on Computational Creativity, 2013

Music cognition: Bridging computation and insights from cognitive neuroscience.

Marcus T. Pearce, Martin Rohrmeier, Petri Toiviainen, Elvira Brattico, Psyche Loui, Edward W. Large, Ji-Chul Kim

Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

Predictive processing of musical structure: effects of genre-specific expertise.

Niels Christian Hansen, Peter Vuust, Marcus T. Pearce

Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

An Information-Theoretic Account of Musical Expectation and Memory.

Kat Agres, Samer Abdallah, Marcus T. Pearce

Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

2012

Auditory Expectation: The Information Dynamics of Music Perception and Cognition.

Marcus T. Pearce, Geraint A. Wiggins

Top. Cogn. Sci., 2012

Music Cognition and the Cognitive Sciences.

Marcus T. Pearce, Martin Rohrmeier

Top. Cogn. Sci., 2012

Evaluation of Musical Features for Emotion Classification.

Yading Song, Simon Dixon, Marcus T. Pearce

Proceedings of the 13th International Society for Music Information Retrieval Conference, 2012

2010

Melodic Grouping in Music Information Retrieval: New Methods and Applications.

Marcus T. Pearce, Daniel Müllensiefen, Geraint A. Wiggins

Proceedings of the Advances in Music Information Retrieval, 2010

Unsupervised statistical learning underpins computational, behavioural, and neural manifestations of musical expectation.

Marcus T. Pearce, María Herrojo Ruiz, Selina Kapasi, Geraint A. Wiggins, Joydeep Bhattacharya

NeuroImage, 2010

Development of Techniques for the Computational Modelling of Harmony.

Raymond Whorley, Geraint A. Wiggins, Christophe Rhodes, Marcus T. Pearce

Proceedings of the International Conference on Computational Creativity, 2010

2008

A Comparison of Statistical and Rule-Based Models of Melodic Segmentation.

Marcus T. Pearce, Daniel Müllensiefen, Geraint A. Wiggins

Proceedings of the ISMIR 2008, 2008

2004

The Second International Symposium on Computer Music Modeling and Retrieval (CMMR 2004) Aalborg University Esbjerg, Esbjerg, Denmark, 26-29 May 2004.

Marcus T. Pearce, David Meredith

Comput. Music. J., 2004

Methods for Combining Statistical Models of Music.

Marcus T. Pearce, Darrell Conklin, Geraint A. Wiggins

Proceedings of the Computer Music Modeling and Retrieval: Second International Symposium, 2004