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- W2534846975 abstract "This chapter will consider the knowledge gained in the context of speech enhancement, which has been an active field of research for decades. There exist well-established solutions to the problem of enhancing noise-corrupted speech, a wide range of them formulated in the short-time Fourier transform (STFT) domain, motivated by its mathematical convenience and efficient implementation. Estimation of the clean speech STFT representation has been focused on processing solely the spectral amplitude, leaving the spectral phase untouched. From the perceptual point of view, an accurate estimate of the clean speech spectral amplitude is indispensable. In addition, the spectral phase was found to be perceptually irrelevant by Wang and Lim in 1982, leading the subsequent research to neglect the information carried by the spectral phase. It is interesting that at the same time, they stated that a reasonable phase estimate could be beneficial if used for refinement of the amplitude estimation. More recent findings revealed contradictory results, conceding perceptual importance to the spectral phase. Starting from this study, the information carried by the spectral phase gained more and more attention in the application of speech enhancement. Within the class of STFT-based approaches, there exist various possibilities to formulate the speech enhancement problem. This chapter considers the class of statistical estimators; more precisely, we will focus on methods that make use of the minimum mean square error criterion. Starting from general concepts used in speech enhancement systems, we will illustrate how additional knowledge about the spectral phase can be incorporated into the estimation framework in order to push the limits of phase-insensitive approaches." @default.
- W2534846975 created "2016-10-28" @default.
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- W2534846975 date "2016-10-21" @default.
- W2534846975 modified "2023-10-14" @default.
- W2534846975 title "Phase Processing for Single‐Channel Speech Enhancement" @default.
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- W2534846975 doi "https://doi.org/10.1002/9781119238805.ch4" @default.
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