Estimation the Number of Speakers Based on Adaptive Wavelet Transform by Generalized Eigenvalue Decomposition and K-means Clustering

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dc.contributor.authorFiroozabadi, Ali
dc.contributor.authorIrarrazaval Mena, Pablo
dc.contributor.authorAdasme, Pablo
dc.contributor.authorDurney, Hugo
dc.contributor.authorOlave, Miguel
dc.contributor.authorAzurdia-Meza, Cesar
dc.date.accessioned2022-05-16T13:00:31Z
dc.date.available2022-05-16T13:00:31Z
dc.date.issued2019
dc.description.abstractThe aim of this paper is estimation the number of simultaneous speakers from the overlapped speech signals. The proposed method in this paper is based on spectrum estimation with adaptive wavelet transform in combination with generalized eigenvalue decomposition (GEVD) and K-means clustering. Firstly, the spectral estimation method is implemented on all microphone signals to select the best part of signal spectrum. In following, the microphone signals are divided to different subbands by using of adaptive wavelet transform. The GEVD algorithm is implemented on each microphone pairs in different subband to estimate the room impulse response and time difference of arrival (TDOA). Finally, the K-means clustering with silhouette criteria is used to estimate the number of speakers (K value). The proposed algorithm is implemented on simulated and real data to show the superiority of the proposed method in comparison with other previous works.
dc.fuente.origenIEEE
dc.identifier.doi10.1109/ICSPCS47537.2019.9008480
dc.identifier.eisbn9781728121949
dc.identifier.isbn781728121956
dc.identifier.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9008480
dc.identifier.urihttps://doi.org/10.1109/ICSPCS47537.2019.9008480
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/63939
dc.information.autorucEscuela de ingeniería ; Irarrazaval Mena, Pablo ; S/I ; 57376
dc.language.isoen
dc.nota.accesoContenido parcial
dc.publisherIEEE
dc.relation.ispartofInternational Conference on Signal Processing and Communication Systems (ICSPCS) (13° : 2019 : Gold Coast, Australia)
dc.rightsacceso restringido
dc.subjectEstimation
dc.subjectWavelet transforms
dc.subjectClustering algorithms
dc.subjectMicrophone arrays
dc.subjectEigenvalues and eigenfunctions
dc.titleEstimation the Number of Speakers Based on Adaptive Wavelet Transform by Generalized Eigenvalue Decomposition and K-means Clusteringes_ES
dc.typecomunicación de congreso
sipa.codpersvinculados57376
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