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Martin Rohrmeier
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2020 – today
- 2023
- [j10]Gabriele Cecchetti, Cédric A. Tomasini, Steffen A. Herff, Martin A. Rohrmeier:
Interpreting Rhythm as Parsing: Syntactic-Processing Operations Predict the Migration of Visual Flashes as Perceived During Listening to Musical Rhythms. Cogn. Sci. 47(12) (2023) - [j9]Johannes Hentschel, Martin Rohrmeier:
ms3: A parser for MuseScore files, serving as data factory for annotated music corpora. J. Open Source Softw. 8(88): 5195 (2023) - [c33]Gabriele Cecchetti, Christoph Finkensiep, Xinyi Guan, Steffen A. Herff, Anna Fiveash, Claire Pelofi, John E. Drury, Martin A. Rohrmeier:
Music Cognition between Theory and Experiment. CogSci 2023 - [c32]Mark Gotham, Johannes Hentschel, Louis Couturier, Nathan Dykeaylen, Martin Rohrmeier, Mathieu Giraud:
The 'Measure Map': an inter-operable standard for aligning symbolic music. DLfM 2023: 91-99 - [c31]Christoph Finkensiep, Matthieu Haeberle, Friedrich Eisenbrand, Markus Neuwirth, Martin Rohrmeier:
Repetition-Structure Inference With Formal Prototypes. ISMIR 2023: 383-390 - [c30]Johannes Hentschel, Andrew McLeod, Yannis Rammos, Martin Rohrmeier:
Introducing DiMCAT for Processing and Analyzing Notated Music on a Very Large Scale. ISMIR 2023: 516-523 - [c29]Zeng Ren, Wulfram Gerstner, Martin Rohrmeier:
Music as Flow: A Formal Representation of Hierarchical Processes in Music. ISMIR 2023: 627-633 - 2022
- [j8]Gabriele Cecchetti, Steffen A. Herff, Martin A. Rohrmeier:
Musical Garden Paths: Evidence for Syntactic Revision Beyond the Linguistic Domain. Cogn. Sci. 46(7) (2022) - [j7]Martin Rohrmeier:
On Creativity, Music's AI Completeness, and Four Challenges for Artificial Musical Creativity. Trans. Int. Soc. Music. Inf. Retr. 5(1): 50-66 (2022) - [c28]Andrew McLeod, Xavier Suermondt, Yannis Rammos, Steffen A. Herff, Martin A. Rohrmeier:
Three Metrics for Musical Chord Label Evaluation. FIRE 2022: 47-53 - 2021
- [j6]Johannes Hentschel, Markus Neuwirth, Martin Rohrmeier:
The Annotated Mozart Sonatas: Score, Harmony, and Cadence. Trans. Int. Soc. Music. Inf. Retr. 4(1): 67-80 (2021) - [c27]Gabriele Cecchetti, Steffen A. Herff, Martin A. Rohrmeier:
Musical syntactic structure improves memory for melody: evidence from the processing of ambiguous melodies. CogSci 2021 - [c26]Daniel Harasim, Christoph Finkensiep, Louis Bigo, Mathieu Giraud, Florence Levé, David R. W. Sears, Daniel Shanahan, Martin A. Rohrmeier:
Music Cognition: The Complexity of Musical Structure. CogSci 2021 - [c25]Daniel Harasim, Timothy J. O'Donnell, Martin A. Rohrmeier:
The Learnability of Goal-directedness in Jazz Music. CogSci 2021 - [c24]Steffen A. Herff, Daniel Harasim, Gabriele Cecchetti, Christoph Finkensiep, Martin A. Rohrmeier:
Hierarchical syntactic structure predicts listeners' sequence completion in music. CogSci 2021 - [c23]Robert Lieck, Leona Wall, Martin A. Rohrmeier:
Discretisation and Continuity: Simulating the Emergence of Symbols in Communication Games. CogSci 2021 - [c22]Christoph Finkensiep, Martin Rohrmeier:
Modeling and Inferring Proto-Voice Structure in Free Polyphony. ISMIR 2021: 189-196 - [c21]Johannes Hentschel, Fabian C. Moss, Markus Neuwirth, Martin Rohrmeier:
A semi-automated workflow paradigm for the distributed creation and curation of expert annotations. ISMIR 2021: 262-269 - [c20]Andrew McLeod, Martin Rohrmeier:
A Modular System for the Harmonic Analysis of Musical Scores using a Large Vocabulary. ISMIR 2021: 435-442 - [c19]Martin Rohrmeier, Fabian C. Moss:
A Formal Model of Extended Tonal Harmony. ISMIR 2021: 569-578 - [c18]Robert Lieck, Martin Rohrmeier:
Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks. NeurIPS 2021: 4370-4383 - [i2]Robert Lieck, Martin Rohrmeier:
Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks. CoRR abs/2111.01853 (2021) - 2020
- [j5]Robert Lieck, Fabian C. Moss, Martin Rohrmeier:
The Tonal Diffusion Model. Trans. Int. Soc. Music. Inf. Retr. 3(1): 153 (2020) - [c17]Daniel Harasim, Christoph Finkensiep, Petter Ericson, Timothy J. O'Donnell, Martin Rohrmeier:
The Jazz Harmony Treebank. ISMIR 2020: 207-215 - [c16]Christoph Finkensiep, Ken Déguernel, Markus Neuwirth, Martin Rohrmeier:
Voice-Leading Schema Recognition Using Rhythm and Pitch Features. ISMIR 2020: 520-526 - [c15]Martin Rohrmeier:
Towards a Formalization of Musical Rhythm. ISMIR 2020: 621-629 - [c14]Robert Lieck, Martin Rohrmeier:
Modelling Hierarchical Key Structure With Pitch Scapes. ISMIR 2020: 811-818 - [c13]Thibault Jaccard, Robert Lieck, Martin Rohrmeier:
AutoScale: Automatic and Dynamic Scale Selection for Live Jazz Improvisation. NIME 2020: 422-427
2010 – 2019
- 2019
- [c12]Daniel Harasim, Timothy J. O'Donnell, Martin Rohrmeier:
Harmonic Syntax in Time: Rhythm Improves Grammatical Models of Harmony. ISMIR 2019: 335-342 - [c11]Christoph Finkensiep, Richard Widdess, Martin Rohrmeier:
Modelling the Syntax of North Indian Melodies with a Generalized Graph Grammar. ISMIR 2019: 462-469 - [c10]Daniel Harasim, Thomas Noll, Martin Rohrmeier:
Distant Neighbors and Interscalar Contiguities. MCM 2019: 172-184 - [i1]Willem H. Zuidema, Dieuwke Hupkes, Geraint A. Wiggins, Constance Scharff, Martin Rohrmeier:
Formal models of Structure Building in Music, Language and Animal Songs. CoRR abs/1901.05180 (2019) - 2018
- [j4]Markus Neuwirth, Daniel Harasim, Fabian C. Moss, Martin Rohrmeier:
The Annotated Beethoven Corpus (ABC): A Dataset of Harmonic Analyses of All Beethoven String Quartets. Frontiers Digit. Humanit. 5: 16 (2018) - [c9]Daniel Harasim, Martin Rohrmeier, Timothy J. O'Donnell:
A Generalized Parsing Framework for Generative Models of Harmonic Syntax. ISMIR 2018: 152-159 - [c8]Christoph Finkensiep, Markus Neuwirth, Martin Rohrmeier:
Generalized Skipgrams for Pattern Discovery in Polyphonic Streams. ISMIR 2018: 547-553 - 2017
- [j3]Martin Rohrmeier, Richard Widdess:
Incidental Learning of Melodic Structure of North Indian Music. Cogn. Sci. 41(5): 1299-1327 (2017) - [c7]Jonas Langhabel, Robert Lieck, Marc Toussaint, Martin Rohrmeier:
Feature Discovery for Sequential Prediction of Monophonic Music. ISMIR 2017: 649-656 - 2013
- [c6]Marcus T. Pearce, Martin Rohrmeier, Petri Toiviainen, Elvira Brattico, Psyche Loui, Edward W. Large, Ji-Chul Kim:
Music cognition: Bridging computation and insights from cognitive neuroscience. CogSci 2013 - [c5]Patrick Rebuschat, Martin Rohrmeier, Morten H. Christiansen, Zoltan Dienes, Daniele Schön, Jennifer Misyak, Clément François, Xiuyan Guo, Feifei Li, Richard Widdess:
Implicit Learning Out of the Lab: Language and Music. CogSci 2013 - 2012
- [j2]Marcus T. Pearce, Martin Rohrmeier:
Music Cognition and the Cognitive Sciences. Top. Cogn. Sci. 4(4): 468-484 (2012) - [j1]Martin Rohrmeier, Patrick Rebuschat:
Implicit Learning and Acquisition of Music. Top. Cogn. Sci. 4(4): 525-553 (2012) - 2011
- [c4]Thomas Hedges, Martin Rohrmeier:
Exploring Rameau and Beyond: A Corpus Study of Root Progression Theories. MCM 2011: 334-337
2000 – 2009
- 2009
- [c3]Justin Salamon, Martin Rohrmeier:
A Quantitative Evaluation of a Two Stage Retrieval Approach for a Melodic Query by Example System. ISMIR 2009: 255-260 - [c2]W. Bas de Haas, Martin Rohrmeier, Remco C. Veltkamp, Frans Wiering:
Modeling Harmonic Similarity Using a Generative Grammar of Tonal Harmony. ISMIR 2009: 549-554 - 2000
- [c1]Martin Rohrmeier:
Interactive simulation using virtual systems: web based robot simulation using VRML. WSC 2000: 1525-1528
Coauthor Index
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