Statistical Sinusoidal Modeling for Expressive Sound Synthesis

Henrik von Coler
DAFx-2019 - Birmingham
Statistical sinusoidal modeling represents a method for transferring a sample library of instrument sounds into a data base of sinusoidal parameters for the use in real time additive synthesis. Single sounds, capturing an instrument in combinations of pitch and intensity, are therefor segmented into attack, sustain and release. Partial amplitudes, frequencies and Bark band energies are calculated for all sounds and segments. For the sustain part, all partial and noise parameters are transformed to probabilistic distributions. Interpolated inverse transform sampling is introduced for generating parameter trajectories during synthesis in real time, allowing the creation of sounds located at pitches and intensities between the actual support points of the sample library. Evaluation is performed by qualitative analysis of the system response to sweeps of the control parameters pitch and intensity. Results for a set of violin samples demonstrate the ability of the approach to model dynamic timbre changes, which is crucial for the perceived quality of expressive sound synthesis.