Journals and conferences

• Proceedings of recent ICMCs

Sadly, the following use the (horrible, rip-off) "pay to view" model:

• Music Analysis
• Music Perception
• Musicae Scientiae
• Journal of new music research

Nuance

I subdivide this as follows:

"Nuance analysis": studying a corpus of performances.

• Statistical: study the statistics of the nuance.
• Model-based: find specific parameterized functions that fit the data.

"Nuance generation": adding nuance to a rendition.

• AI-based: train a neural net with a corpus of performances.
• Algorithmic: add nuance with deterministic rules based on pitch contour etc.
• Explicit: a human specifies nuance.

These are related; e.g. a system for explicit nuance generation provides a set of primitives, and ideally these would be chosen based on model-based analysis.

Manfred Clynes and Superconductor

Manfred Clynes did work on explicit (and possibly algorithmic) nuance generation, in the context of a Windows program called SuperConductor (not related to SuperCollider AFAIK). Superconductor does audio synthesis (e.g. of bowed string sounds). It provides control (through a GUI) of high-level (e.g. crescendi) and note-level (e.g. vibrato) nuance. It supports nonlinear curves (exponentials, cubic splines?). It looks rigid and limited. It comes with a few pieces by "The Great Composers" (in a proprietary format) that you can add nuance to. It can also import/export MIDI.

There are a bunch of examples on YouTube, mostly from string quartets. These are not bad - they have nuance with appropriate general properties. However, the nuance is excessive, and it's clear within a few seconds that it's computer-generated.

This is based on Clynes' theory of acoustic aesthetics/emotion called "Sentic forms", which holds that composers have characteristic "hierarchical pulses". This is pretty vague and speculative. Also, all of Clynes' stuff (including his self-authored Wikipedia page) has an uncomfortably high level of self-promotion.

Papers by Clynes:

• The hidden code of musicality

Bruno Repp

• A microcosm of musical expression. I. Quantitative analysis of pianists’ timing in the initial measures of Chopin’s Etude in E major . The Journal of the Acoustical Society of America, 1998
• A microcosm of musical expression: II. Quantitative analysis of pianists’ dynamics in the initial measures of Chopin’s Etude in E major Journal of the Acoustical Society of America, Vol. 105 pp. 1972-1988
• A microcosm of musical expression. III. Contributions of timing and dynamics to the aesthetic impression of pianists' performances of the initial measures of Chopin's Etude in E Major. Journal of the Acoustical Society of America, Vol. 106 pp. 469-478
• Music, mind, and science. XVI. Individual differences in the expressive shaping of a musical phrase: The opening of Chopin’s etude in E major
• Detecting deviations from metronomic timing in music: Effects of perceptual structure on the mental timekeeper Perception & Psychophysics, Vol. 61 (3) pp. 529-548
• Relationships between performance timing, perception of timing perturbations, and perceptual-motor synchronisation in two Chopin preludes Australian Journal of Psychology, Vol. 51 (No. 3) pp. 188-203
• Variations on a Theme by Chopin: Relations Between Perception and Production of Timing in Music. Human Perception and Performance, Journal of Experimental Psychology, Vol. 24 (No. 3) pp. 791-811, 1998
• Expressive timing in a Debussy prelude: A comparison of student and expert pianists . Musicae Scientiae, Vol. 1 (2) pp. 257-268.
• Effects of tempo on the timing of simple musical rhythms. Music Perception, Vol. 19 (No. 4) pp. 565-593
• The timing implication of musical structures. In D. Greer (Ed.), Musicology and Sister Disciplines, Past, Present, Future, pp. 60-70
• Manfred Clynes, pianist In:, A Festschrift for Manfred Clynes. St. Louis, MO: MMB Music, pp. 70-84
• Patterns of note onset asynchronies in expressive piano performance. Journal of the Acoustical Society, Vol. 100 (6) pp. 3917-3932, 1996
• Pedal timing and tempo in expressive piano performance: A reliminary investigation. Psychology of Music, Vol. 24 pp. 199-221, 1996
• The art of inaccuracy: Why pianists' errors are difficult to hear. Music Perception, Vol. 14 (2) pp. 161-184, 1996
• The dynamics of expressive piano performance: Schumann’s “Träumerei” revisited. J. Acoust. Soc. Am, Vol. 100 (1) pp. 641-650, 1996
• Quantitative effects of global tempo on expressive timing in music performance: Some perceptual evidence. Music Perception, Vol. 13 (No. 1) pp. 39-57, 1995
• Expressive timing in Schumann’s “Träumerei:” an analysis of performances by graduate student pianists. J. Acoust. Soc. Am, Part 1, November, Vol. 98 (5) pp. 2413-2427, 1995
• Relational invariance of expressive microstructure across global tempo changes in music performance: An exploratory study. Psychological Research, Vol. 56 pp. 299-284, 1994
• A Constraint on the Expressive Timing of a Melodic Gesture: Evidence from Performance and Aesthetic Judgment. Music Perception, Vol. 10 (2) pp. 221-242, 1993
• Diversity and commonality in music performance: An analysis of timing microstructure in Schumann's “Traumerei”. Journal of the Acoustical Society of America, Vol. 92 (5) pp. 2546-2568, 1992
• Composers' Pulses: Science or Art?. Music Perception, 13, Vol. 7 (4) pp. 423-434, 1990
• Patterns of expressive timing in performances of a Beethoven minuet by nineteen famous pianists. Published 1 May 1988, The Journal of the Acoustical Society of America
• Expressive Microstructure in Music: A Preliminary Perceptual Assessment of Four Composers' "Pulses". Music Perception, Vol. 6 (3) pp. 243-274, 1989
• The Detectability of Local Deviations from a Typical Expressive Timing Pattern. Music Perception, 1998

Data

• MAESTRO: a corpus of piano performances (MIDI file and audio).

Others

Papers that study performance nuance, and show actual data.

• A Musical Microscope Applied to the Piano Playing of Vladimir de Pachmann . Nigel Nettheim, 2001. Compares several performances of the start of a Chopin Nocturne. Uses interesting score notation that shows timing and dynamics.
• Corpus analysis of rubato in Bach C prelude. Studies the average lengths of pauses: the larger the phrase unit, the longer the pause. Also compares various performers. Looks at Traumerei also. Worth reading.
• A Three-Dimensional Model for Evaluating Individual Differences in Tempo and Tempo Variation in Musical Performance. Zhou and Fabian. Musicae Scientiae, 2019. nal_coloring_of_computer_controlle.pdf
• Modeling and control of expressiveness in music performance. Canazza et al. PROCEEDINGS OF THE IEEE, VOL. 92, NO. 4, APRIL 2004.
• A Survey of Computer Systems for Expressive Music Performance. Kirke and Miranda, ACM Computing Surveys,Volume 42Issue 1December 2009
• Emotional coloring of computer-controlled music performances. Bresin and Friberg. CMJ, 2000
• Investigating pianists' individuality in the performance of five timbral nuances through patterns of articulation, touch, dynamics, and pedaling. Bernays and Traube. Frontiers in Psychology, 2014.
• Computational Models of Expressive Music Performance: The State of the Art. Widmer and Goeble. September 2004, Journal of New Music Research 33(3):203-216
• Computational models of expressive music performance: a comprehensive and critical review. Cancino-Chacon et al. Frontiers in digital humanities, 2018.
• Sources of timing variations in music performance: A psychological segmentation model. Penel and Drake. Psychol Res 1998
• Force Dynamics of Tempo Change in Music Jacob Feldman, David Epstein and Whitman Richards. Music Perception: An Interdisciplinary Journal , Winter, 1992, Vol. 10, No. 2 (Winter, 1992), pp. 185-203
• In Search of the Horwitz Factor. Widmer et al. AI Magazine 2003.
• Analysis of timing variation
• final ritardando
• Retard and physical motion
• Anatomy of the retard
• Performing Bach's Keyboard Music - Phrasing, George Kochevitsky, 1972
• Music Performance Research at the Millennium. Gabrielsson. Psychology of Music ; Manchester Vol. 31, Iss. 3, (Jul 2003): 221-272.
• A Model of Expressive Timing in Tonal Music, Neil Todd, Music Perception, 1985. Nuance as a function of musical structure ("time-span reduction")
• The dynamics of dynamics: A model of musical expression. Neil P. McAngus Todd. The Journal of the Acoustical Society of America 91, 3540 (1992)
• Performance analysis and Chopin's mazurkas. Nicholas Cook. Musicae Scientiae, 2007
• Methodologies for Expressiveness Modeling of and for Music Performance Giovanni De Poli. 2004, Journal of New Music Research.
• A state of the art on computational music performance. Miguel Delgado et al. Expert Systems with Applications, 2010
• Overview of the KTH rule system for musical performance. Anders Friberg et al. Advances in Cognitive Psychology. 2006.
• Playing Mozart by Analogy: Learning Multilevel Timing and Dynamics Strategies G. Widmer. Journal of New Music Research 32(3):259-268, September 2003
• Expressive gesture in Grieg’s recordings of two Op. 43 Lyric Pieces: An exploratory principal components analysis. Georgia Volioti, Music Performance Research, 2019
• Expressiveness in Music Performance: Empirical approaches across styles and cultures Dorottya Fabian, (Oxford: OUP 2014), 58-79
• Audio Morphing Different Expressive Intentions for Multimedia Systems Canazza, De Poli, Drioli, Roda. July 2000 IEEE Multimedia 7(3):79-83.
• An Interdisciplinary Review of Music Performance Analysis Pati, Lerch et al. November 2020 Transactions of the International Society for Music Information Retrieval 3(1):221-245

Taylor & Francis: no Semantic scholar: sometimes researchgate: sometimes booksc.me: yes (arabic)

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