A framework for real-time expressive modification of audio musical performances is presented. An expressiveness model compute the deviations of the musical parameters which are relevant in terms of control of the expressive intention. The modifications are then realized by the integration of the model with a sound processing engine.

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We propose an original technique for separating the spectrum of the noisy residual component from that of the harmonic, quasideterministic one, and to estimate the envelope of the residual, for the spectrum modeling of musical sounds. The algorithm for spectrum separation relies on nonlinear transformations of the amplitude spectrum of the sampled signal (obtained via FFT), which allow to eliminate the dominant partials without the need for precisely tuned notch filters. The envelope estimation is performed by calculating the energy of the signal in the frequency domain, over a sliding time window. Eventually the residual can be obtained by combining its spectrum and envelope, so that separate processing can be performed on the two.

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In this paper, an analysis of flute attacks processed by a model of the physiological auditory system is presented. In flute performance, the musician uses consonants (/d/, /g/, /k/, /t/ and /p/) in order to create particular effects as hard and soft attacks. These effects are very important in music interpretation. We found that the model discriminates the sounds very well and better than spectral analysis as worked out by standard methods. The model responses appeared very detailed and allowed attack classification by the application of very simple pattern recognition techniques.

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This paper presents the results of an experiment aimed to evaluate the quality of different audio restoration algorithms based on different Short Time Spectral Attenuation methods. To single out the best computational methodologies for audio restoration an experiment was made, implementing a software (in DirectX plug-in form) which uses different algorithms. The software, working in real time, permits to compare the different algorithms in a objective way: in fact, it is possible to use the same software environment to operate the restorations with different algorithms. In this way, is feasible to compare different methods. In the paper we will first shortly overview the most used audio restoration methods and, in particular, the algorithms implemented in our software. Then we will present a timefrequency analysis of the restored stimuli to show the main advantages and drawbacks of the different algorithms used.

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