The Research On Audio Signal Modeling With Sinusoids Plus Noise

Because audio signal is a nonstationary signals, the aim of build audio signal spectrum modeling is to transform a signal to a more easily applicable form, removing the information that is irrelevant in signal perception. Sinusoids plus noise model is a spectral model, in which the periodic components of the sound are represented with sinusoids with time-varying frequencies, amplitudes and phases. The remaining non-periodic components are represented with a filtered noise. In the case of polyphonic music signals, the estimation of the parameters of sinusoids is a difficult task, since the periodic components are usually not stable. A sufficient time and frequency resolution is also difficult to achieve at the same time. A big part of this thesis discusses the detection and parameter estimation of periodic components with several algorithms. In addition to already existing algorithms, a new iterative algorithm is presented, which is based on the fusion of closely spaced sinusoids. Also a new separation method based on the multipitch estimation is explained.