Download Enhanced partial tracking using linear prediction In this paper, we introduce a new partial tracking method suitable for the sinusoidal modeling of mixtures of instrumental sounds with pseudo-stationary frequencies. This method, based on the linear prediction of the frequency evolutions of the partials, enables us to track these partials more accurately at the analysis stage, even in complex sound mixtures. This allows our spectral model to better handle polyphonic sounds.
Download Enhanced Time-Stretching Using Order-2 Sinusoidal Modeling In this article, we introduce a 2-level sinusoidal model and demon strate its aptitude for a challenging digital audio effect: time-stretching without audible artifacts. More precisely, sinusoidal modeling is used at the two levels of the new sound model. We consider the frequency and amplitude parameters of the partials of the classic sinusoidal model as (control) signals, that we propose to model again using a sinusoidal model. This way, higher-level musical structures such as the vibrato and tremolo in the original sound are captured in the “partials of partials” of this order-2 sinusoidal model. We propose then a new time-stretching method, based on this new hierarchical model, which preserves not only the pitch of the original sound, but also its natural vibrato and tremolo.
Download A Generalized Polynomial and Sinusoidal Model for Partial Tracking and Time Stretching In this article, we introduce a new generalized model based on polynomials and sinusoids for partial tracking and time stretching. Nowadays, most partial tracking algorithms are based on the McAulay-Quatieri approach and use polynomials for phase, frequency, and amplitude tracks. Some sinusoidal approaches have also been proved to work in certain conditions. We will present here an unified model using both approaches, which will allow more flexible partial tracking and time stretching.