Despite the complex multi‐dimensional nature of musical expression in the final analysis, musical expression is conveyed by sound. Therefore the expressiveness of music must be present in the sound and therefore should be observable as fundamental and emergent features of the sonic signal. To gain insight into this feature space, a real‐time visualization tool has been developed. The fundamental physical features—pitch, dynamic level, and timbre (as represented by spectral energy distribution)—are extracted from the audio signal and displayed versus time in a real‐time animation. Emergent properties of the sound, such as musical attacks and releases, the dynamic shaping of musical lines, timing of note placements, and the subtle modulation of the tone, loudness, and timbre can be inferred from the fundamental feature set and presented to the user visually. This visualization tool provides a stimulating music performance‐learning environment to help musicians achieve their artistic goals more effectively. Such visualizations and interactions with musical sound also will promote the semantic understanding of an expressive musical language.
Skip Nav Destination
Article navigation
March 2010
Meeting abstract. No PDF available.
March 23 2010
The shape of musical sound: Real‐time visualizations of expressiveness in music performance.
Gang Ren;
Gang Ren
Dept. of Elec. and Comput. Eng., Edmund A. Hajim School of Eng. and Appl. Sci., Univ. of Rochester, Rochester, NY 14627
Search for other works by this author on:
Justin Lundberg;
Justin Lundberg
Univ. of Rochester, Rochester, NY
Search for other works by this author on:
Mark F. Bocko;
Mark F. Bocko
Univ. of Rochester, Rochester, NY
Search for other works by this author on:
Dave Headlam
Dave Headlam
Univ. of Rochester, Rochester, NY
Search for other works by this author on:
J. Acoust. Soc. Am. 127, 1983 (2010)
Citation
Gang Ren, Justin Lundberg, Mark F. Bocko, Dave Headlam; The shape of musical sound: Real‐time visualizations of expressiveness in music performance.. J. Acoust. Soc. Am. 1 March 2010; 127 (3_Supplement): 1983. https://doi.org/10.1121/1.3385099
Download citation file:
Citing articles via
A survey of sound source localization with deep learning methods
Pierre-Amaury Grumiaux, Srđan Kitić, et al.
Variation in global and intonational pitch settings among black and white speakers of Southern American English
Aini Li, Ruaridh Purse, et al.
Related Content
Extracting heterogeneous structured features from music performance
J Acoust Soc Am (October 2011)
Shaping musical vibratos using multi-modal pedagogical interactions
J Acoust Soc Am (October 2014)
Pitch discrimination is better for synthetic timbre than natural musical instrument timbres despite familiarity
J. Acoust. Soc. Am. (July 2022)
Audience-participatory music performance system featuring hand gesture interpretation
AIP Conf. Proc. (November 2023)
The influence of cellist's postural movements on their musical expressivity
J Acoust Soc Am (May 2017)