Multi-pitch estimation based on multi-scale product analysis, improved comb filter and dynamic programming

Zeremdini, Jihen; Messaoud, Mohamed Anouar Ben; Bouzid, Aïcha

doi:10.1007/s10772-017-9398-0

Cited by 3 publications

(1 citation statement)

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“…Besides, multi-pitch estimation based on multi-scale product analysis, improved comb filter and dynamic programming approach is about "a method consists on the autocorrelation function of the multi-scale product calculation of the mixture signal, its filtered version by a rectangular improved comb filter and the dynamic programming of the residual signal spectral density for multi-pitch detection" [26].…”

Section: Related Workmentioning

confidence: 99%

Improved comb filter for the separation of the voiced speech signals in the case of two speakers

2019

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In this paper, we present a method for separating voiced sounds from a composite signal. This method is mainly based on the separation by modified comb filter. This filter is keyed to the average values of the estimated pitch. This estimation is performed through an autocorrelation of multi-scale product analysis to separate the effects of the source and the vocal tract. The "autocorrelation of the multi-scale product" method allows noise elimination and the apparition of a signal periodic structure. Peaks that appear are used to calculate the mean fundamental frequency of the target speaker which will be used in the corresponding comb filters to determine the target speaker contribution. After the subtraction of this contribution from the mixture, we obtain the intrusion speaker. This separation is validated by its application on Cooke database and a part of VCTK database and compared to recent methods as Wang-Brown, Hu-Wang, Zhang-Liu and Quan systems. Results confirm the performance of the proposed approach.

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Section: Related Workmentioning

confidence: 99%