Spectral analysis for nonstationary audio
Résumé
A new approach for the analysis of nonstationary signals is proposed, with a focus on audio applications. Following earlier contributions, nonstationarity 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 paper provides theoretical analysis of the approximations, and describes and analyzes a corresponding estimation algorithm. The latter is tested and validated on synthetic as well as real audio signal.
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MeyTor17.pdf (533.86 Ko)
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UnWarp.zip (5.75 Mo)
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supplementary_material.pdf (418.19 Ko)
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