Synthesise realistic sound by modelling the physics of vibration.
Physics-Based Synthesis: Modeling Vibrations and Timbre teaches a distinctive approach to making sound: rather than sampling or shaping waveforms, you model the physics that produces them. You learn how vibrating strings, membranes, air columns and resonant bodies generate timbre, and the computational methods that simulate them — from mass-spring and modal models to digital waveguides. The course connects acoustics to implementation, so you can build synthesis models that respond naturally to how they are played. You finish able to design and implement a physically modelled sound. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
This course covers physics-based sound synthesis — modelling the vibrations and acoustics of real instruments and objects to generate realistic sound computationally.
1. Explain how vibration and resonance produce timbre.
2. Model strings, membranes and air columns.
3. Implement mass-spring, modal and waveguide synthesis.
4. Map physical parameters to expressive control.
5. Build a physically modelled instrument sound.
• Audio developers and sound designers
• Musicians and technologists in DSP
• Researchers in acoustics and computer music
• Students specialising in audio computing
• The ability to build a physics-based synthesis model.
• An understanding of acoustics for sound design.
• A computational-audio project.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
• Modes, harmonicity and inharmonicity in strings, bars and membranes
• Excitation, resonance and radiation as three separable stages
• Why sampling reproduces a sound but not the instrument behaviour
• Mass-spring-damper networks and finite difference schemes
• Stability conditions and the Courant limit on step size
• Numerical dispersion and the computational cost of accuracy
• Digital waveguides, delay lines and travelling wave decomposition
• Karplus-Strong as the minimal plucked string, and its extensions
• Fractional delay, loop filters and tuning the model correctly
• Modal decomposition into parallel resonators
• Estimating modal parameters from recordings of real objects
• Trading mode count against realism and CPU cost
• Bow, reed and hammer interaction models and their nonlinear regimes
• Coupling between strings and body, and sympathetic resonance
• Mapping controller input to physical parameters for expressive play
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | Jupyter Notebook |
| Covered Tool / Platform | Google Colab |
| Covered Tool / Platform | Microsoft Excel |
| Covered Tool / Platform | Relevant Online Databases |
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