Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hodaya Hammer"'
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2021, Iss 1, Pp 1-10 (2021)
Abstract In this study, we present a deep neural network-based online multi-speaker localization algorithm based on a multi-microphone array. Following the W-disjoint orthogonality principle in the spectral domain, time-frequency (TF) bin is dominate
Externí odkaz:
https://doaj.org/article/65f5263b056245d0901e2e1a6c0a5ad7
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2021, Iss 1, Pp 1-10 (2021)
In this study, we present a deep neural network-based online multi-speaker localization algorithm based on a multi-microphone array. Following the W-disjoint orthogonality principle in the spectral domain, time-frequency (TF) bin is dominated by a si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03e07da0fa94a01aaf696e1b5e031c11
https://doi.org/10.1186/s13636-021-00203-w
https://doi.org/10.1186/s13636-021-00203-w
Publikováno v:
EUSIPCO
In this paper, we present a multi-microphone speech separation algorithm based on masking inferred from the speakers direction of arrival (DOA). According to the W-disjoint orthogonality property of speech signals, each time-frequency (TF) bin is dom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dbe87a3952f86e44fd53314d970d292e
https://doi.org/10.23919/eusipco.2019.8903121
https://doi.org/10.23919/eusipco.2019.8903121
Publikováno v:
2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE).
In this paper we present a mixture of Gaussians-deep neural network (MoG-DNN) algorithm for single-microphone speech enhancement. We combine between the generative mixture of Gaussians (MoG) model and the discriminative deep neural network (DNN). The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a88947411c90f441567813297564622d
https://doi.org/10.1109/icsee.2018.8646105
https://doi.org/10.1109/icsee.2018.8646105