Abstract
Several methods which are used for speech detection usually fail when SNR is low. The wavelet analysis has properties which can help in separating the speech from other signals. Many works report better detection and separation performance using wavelet analysis than using other techniques. On another level, as segmentation of speech into many classes is so hard, WT is well localized in time-frequency domain, and boundaries of speech segments can be willingly detected.
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Farouk, M.H. (2018). Speech Detection and Separation. In: Application of Wavelets in Speech Processing. SpringerBriefs in Electrical and Computer Engineering(). Springer, Cham. https://doi.org/10.1007/978-3-319-69002-5_5
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DOI: https://doi.org/10.1007/978-3-319-69002-5_5
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