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Spectral analysis for non-stationary audio

A new approach for the analysis of non-stationary signals is proposed, with a focus on audio applications. Following earlier contributions, non-stationarity is modeled via stationarity-breaking operators acting on Gaussian stationary random signals. The focus is here on time warping and amplitude modulation, and an approximate maximum-likelihood approach based on suitable approximations in the wavelet transform domain is developed. This papers provides theoretical analysis of the approximations, and describes and analyses a corresponding 
estimation algorithm. The latter is tested and validated on synthetic as well as real audio signal.