### ASA 124th Meeting New Orleans 1992 October

## 5aMU4. The algorithmic sampler: An analysis problem?

**D. Arfib
**

**
**
*CNRS-LMA, 31 chemin J. Aiguier, 13402 Marseille Cedex 09, France
*

*
*
**Ph. Guillemain
**

**
**
*DIGILOG, 13852 Aix-en-Provence Cedex 3, France
*

*
*
**R. Kronland-Martinet
**

**
**
*CNRS-LMA, 13402 Marseille Cedex 09, France
*

*
*
To play natural sounds on an algorithmic synthesizer, it would be
necessary to extract parameters that correspond to a synthesis model from an
analysis of a real sound. The aim of this lecture is to show different facets
of a time-frequency representation that are very particular in the
signal-processing field because they are oriented toward the musical use. For
example, psychoacoustic criteria allow one to ``get rid of'' the incertainty
principle on time and frequency. Here, only the acoustically relevant
parameters are looked for rather than the exact physical data. For that
purpose, time-frequency transforms were used, namely the Gabor and the wavelet
transforms, and additional work on the time-frequency representations they
provide was conducted. For example, the spectral line estimation allows one to
separate each elementary component and to estimate the modulation law
associated to each one by solving a linear system where the coefficients come
from the representation. Special features concerning the sound can be derived
from ridges extracted from the phase diagram; this can lead to the estimation
of frequency modulation laws in a FM model. The evolution of the centroid of
the spectrum can be a good indicator for a synthesis using a wave-shaping
model. The lecture will be accompanied by a lot of time-frequency
representations showing the importance of the choice of the parameters of the
analysis, and the diagrams that one can derivate from them. It will also be
accompanied by sound examples.