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Article Dans Une Revue IEEE/ACM Transactions on Audio, Speech and Language Processing Année : 2018

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 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 introduces JEFAS, a corresponding estimation algorithm. The latter is tested and validated on synthetic as well as real audio signal.
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Dates et versions

hal-01670187 , version 1 (28-12-2017)
hal-01670187 , version 2 (01-06-2018)
hal-01670187 , version 3 (22-08-2018)

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Adrien Meynard, Bruno Torrésani. Spectral Analysis for Nonstationary Audio. IEEE/ACM Transactions on Audio, Speech and Language Processing, 2018, 26 (12), pp.2371 - 2380. ⟨10.1109/TASLP.2018.2862353⟩. ⟨hal-01670187v3⟩
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