Cluster-Weighted Probabilistic Networks for Audio-Synthesis
نویسندگان
چکیده
A cluster-weighted framework is presented that allows powerful and transparent non-linear models to be built by integration of simple local models. Audio synthesis algorithms such as sampling, linear predictive coding and spectral synthesis become globally nonlinear synthesis models that integrate control and sound generation within a single framework. These networks are added additional levels of probabilistic abstraction, e.g. hierarchical structures or Hidden-Markov structures. A system has been implemented that computes the sound of a violin in real time, given the gesture input of a violinist.
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