The Impact of Generated and Expressive Modulation of the Synthetic Instrument Sound Parameters on the Impression of Naturalness

Downloads

Authors

Abstract

Despite their different spectral structures, the sound of early instruments from the electrophone group was often considered to be deceptively similar to the sound of wind or bowed string instruments. However, the wavetable synthesizer playing a short, looped sample of a natural instrument is easily distinguishable from the actual instrument. This results from the presence of specific modulatory structures in the sound of some instruments related to expression, which can be a strong clue regarding the identification of the instrument. The control of early electrophones, such as the theremin or Martenot waves, gave the performer expressive capabilities comparable to bowed instruments. Contemporary synthesizers are returning to similar solutions. The aim of this work is to study the impact of various types of modulation on the perceived naturalness of violin sound. Modulation through an automatic low frequency oscillator is compared to expressive modulation by a human using a controller. Two advanced controllers are studied to determine whether simultaneous modulation of more than one parameter brings benefits. A set of sound samples was prepared which included violin recordings and synthesized signals, where different waveforms were combined with various modulation sources and modulated parameters. The effect was assessed by a group of expert listeners. The results indicate that expressive, multi-parameter modulation with advanced controllers brings benefits for waveforms with realistic spectra, close to that of a violin. In less realistic waveforms

Keywords:

sound synthesis, signal modulation, expressive performance, expressive controller

References


  1. Donati E., Chousidis C. (2022), Electroglottography based real-time voice-to-MIDI controller, Neuroscience Informatics, 2(2): 100041, https://doi.org/10.1016/j.neuri.2022.100041

  2. Fritz C., Stoppani G., Igartua U., Woodhouse J. (2025), Developing methodologies to study perceived sound qualities of violins, Acta Acustica, 9: 32, https://doi.org/10.1051/aacus/2025014

  3. Gurevich M., von Muehlen S. (2001), The accordiatron: A MIDI controller for interactive music, [in:] Proceedings of the International Conference on New Interfaces for Musical Expression, pp. 27–29, https://doi.org/10.5281/zenodo.1176364

  4. Hawley S.H., Chatziioannou V., Morrison A. (2020), Synthesis of musical instrument sounds: Physics-based modeling or machine learning?, Acoustics Today, 16(1): 20–28, https://doi.org/10.1121/AT.2020.16.1.20

  5. Iverson P., Krumhansl C.L. (1993), Isolating the dynamic attributes of musical timbre, Journal of Acoustical Society of America, 94(5): 2593–2603, https://doi.org/10.1121/1.407371

  6. Kim D., Dong H.-W., Jeong D. (2025), ViolinDiff: Enhancing expressive violin synthesis with pitch bend conditioning, [in:] ICASSP 2025 – 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1–5, https://doi.org/10.1109/ICASSP49660.2025.10890613

  7. Liu Q. (2024), An FM-wavetable-synthesized violin with natural vibrato and bow pressure, [in:] Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023), pp. 243–250, https://doi.org/10.2991/978-94-6463-370-2 27.

  8. McAdams S., Bruno G.L. (2012), The perception of musical timbre, [in:] Oxford Handbook of Music Psychology, Hallam S., Cross I., Thaut M.H. [Eds], pp. 72–80, Oxford Library of Psychology, https://doi.org/10.1093/oxfordhb/9780199298457.013.0007

  9. Perez Carrillo A.A. (2009), Enhancing spectral synthesis techniques with performance gestures using the violin as a case study, Ph.D. Thesis, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona.

  10. Robertson A. (2011), Seaboard: A new piano keyboard-related interface combining discrete and continuous control, [in:] Proceedings of the International Conference on New Interfaces for Musical Expression, https://doi.org/10.5281/zenodo.1178081

  11. Schoonderwaldt E., Friberg A. (2001), Towards a rule-based model for violin vibrato, [in:] Proceedings of the Workshop on Current Research Directions in Computer Music, pp. 61–64.

  12. Wu Y. et al. (2022), MIDI-DDSP: Detailed control of musical performance via hierarchical modeling, [in:] International Conference on Learning Representations (ICLR), pp. 1–27.