PHYSICSBASED PARAMETRIC SYNTHESIS OF INHARMONIC PIANO TONES
Jukka Rauhala · Aaltodoc (Aalto University) · 2007
This dissertation studies methods for developing a parametric piano synthesis model using the physics-based approach. The goal is to develop a model that can be controlled with physically meaningful parameters. Moreover, the model is required to be computationally efficient for real-time implementation. The basis of this work is to use the digital waveguide technique for implementing a piano string model. The excitation signal, simulation of dispersion, the beating effect, and simulation of sympathetic resonances are considered. Novel and improved simulation methods are developed for each of these aspects by applying signal processing techniques and knowledge of the human auditory system. The new simulation methods include a novel excitation model with parametric control and the first closed-form design method for dispersion filter design. In addition, two new beating effect simulation methods suitable for parametric real-time synthesis are created. One of the developed methods can be also used for modifying the partial envelopes in recorded tones. Furthermore, an efficient and improved method for simulation of sympathetic resonances has been suggested. Additionally, a novel analysis method for estimating inharmonicity coefficient values from recorded tones, which is needed for high-quality synthesis, is developed giving good results. Finally, a real-time piano synthesis model without any sampled sounds is implemented using the developed simulation methods in collaboration with the Sibelius Academy. The model can be controlled in real-time using physical parameters, such as the fundamental frequency and the inharmonicity coefficient value. The implementation suggests that the goals set for this thesis work are met. The results can be applied to physics-based piano synthesis. The methods can be used to implement a synthesis model for restricted environments, and they can be used to produce test tones for evaluating properties of the human auditory system and testing signal analysis algorithms.