Note:
This bibliographic page is archived and will no longer be updated.
For an up-to-date list of publications from the Music Technology Group see the
Publications list
.
Spectral Modeling Synthesis: A Sound Analysis/Synthesis Based on a Deterministic plus Stochastic Decomposition
| Title | Spectral Modeling Synthesis: A Sound Analysis/Synthesis Based on a Deterministic plus Stochastic Decomposition |
| Publication Type | Journal Article |
| Year of Publication | 1990 |
| Authors | Serra, X. , & Smith J. |
| Journal Title | Computer Music Journal |
| Volume | 14 |
| Issue | 4 |
| Pages | 12-24 |
| Abstract | When generating musical sound on a digital computer, it is important to have a good model whose parameters provide a rich source of meaningful sound transformations. Three basic model types are used widely today far musical sound generation: instrument models, spectrum models, and abstract models. Instrument models attempt to parameterize a sound at its source, such as a violin, clarinet, or vocal tract. Spectrum models attempt to parameterize a sound at the basilar membrane of the ear, discarding whatever information the ear seems to discard in the spectrum. Abstract models, such as FM, attempt to provide musically useful parameters in an abstract formula. This paper addresses the second category of synthesis technique: spectrum modeling. It describes a technique called spectral modeling synthesis (SMS), that models time-varying spectra as (1) a collection of sinusoids controlled through time by piecewise linear amplitude and frequency envelopes ( the deterministic part), and (2) a time-varying filtered noise component ( the stochastic part). The analysis procedure first extracts the sinusoidal trajectories by tracking peaks in a sequence of short-time Fourier transforms. These peaks are then removed by spectral subtraction. The remaining "noise floor" is then modeled as white noise through a time-varying filter. A piecewise linear approximation to the upper spectral envelope of the noise is computed for each successive spectrum, and the stochastic part is synthesized by means of the overlap-add technique. The SMS technique has proved to give general, high-quality transformations far a wide variety of musical signals. |
| preprint/postprint document | http://hdl.handle.net/10230/33796 |
| Final publication | http://doi.org/10.2307/3680788 |
