We employ a hybrid state-space sinusoidal model for general use in analysis-synthesis based audio transformations. This model combines the advantages of a source-filter model with the time-frequency character of the sinusoidal model. We specialize the parameter identification task to a class of ``quasi-harmonic'' sounds. The latter represent a variety of acoustic sources in which multiple, closely spaced modes cluster about principal harmonics loosely following a harmonic structure.
To estimate the sinusoidal parameters, an iterative filterbank splits the signal into subbands, one per principal harmonic. Each filter is optimally designed by a linear programming approach to be concave in the passband, monotonic in transition regions, and to specifically null out sinusoids in other subband regions. Within each subband, instantaneous frequency estimates averaged over all modes in the subband region are used to update the filter's center frequency for the next iteration. In this way, the filterbank progressively adapts to the specific inharmonicity structure of the source recording.
We demonstrate analysis-synthesis applications including standard time and pitch scaling, as well as new effect types exploiting the ``source-filter'' aspect.