Zobrazeno 1 - 10
of 36
pro vyhledávání: '"noise PSD estimation"'
Publikováno v:
Sensors, Vol 24, Iss 12, p 3979 (2024)
A multichannel speech enhancement system usually consists of spatial filters such as adaptive beamformers followed by postfilters, which suppress remaining noise. Accurate estimation of the power spectral density (PSD) of the residual noise is crucia
Externí odkaz:
https://doaj.org/article/56ea3e1c93844ddbb5e06062996cb863
Akademický článek
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Publikováno v:
IEEE Access, Vol 7, Pp 80985-80999 (2019)
Estimation of the noise power spectral density (PSD) plays a critical role in most existing single-channel speech enhancement algorithms. In this paper, we present a novel noise PSD tracking algorithm, which employs a log-spectral power minimum mean
Externí odkaz:
https://doaj.org/article/ecdf2da0d0364480a99c7949f648bc6f
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2017, Iss 1, Pp 1-16 (2017)
Abstract In speech enhancement, noise power spectral density (PSD) estimation plays a key role in determining appropriate de-nosing gains. In this paper, we propose a robust noise PSD estimator for binaural speech enhancement in time-varying noise en
Externí odkaz:
https://doaj.org/article/ff466c0b3a8a489eb8c9eda890c24a9a
Akademický článek
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Publikováno v:
IEEE Access, Vol 7, Pp 80985-80999 (2019)
Estimation of the noise power spectral density (PSD) plays a critical role in most existing single-channel speech enhancement algorithms. In this paper, we present a novel noise PSD tracking algorithm, which employs a log-spectral power minimum mean
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c79f108e19a52a6654d5d591b248704a
https://ieeexplore.ieee.org/document/8740919/
https://ieeexplore.ieee.org/document/8740919/
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2017, Iss 1, Pp 1-16 (2017)
In speech enhancement, noise power spectral density (PSD) estimation plays a key role in determining appropriate de-nosing gains. In this paper, we propose a robust noise PSD estimator for binaural speech enhancement in time-varying noise environment
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e98cc252c489231bfb97b96a50dc7b51
http://link.springer.com/article/10.1186/s13636-017-0122-4
http://link.springer.com/article/10.1186/s13636-017-0122-4
Publikováno v:
Esquivel Jaramillo, A, Nielsen, J K & Christensen, M G 2019, A Study on how Pre-whitening Influences Fundamental Frequency Estimation . in 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019-Proceedings ., 8683653, IEEE, I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, pp. 6495-6499, 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom, 12/05/2019 . https://doi.org/10.1109/ICASSP.2019.8683653
ICASSP
ICASSP
This paper deals with the influence of pre-whitening for the task of fundamental frequency estimation in noisy conditions. Parametric fundamental frequency estimators commonly assume that the noise is white and Gaussian and, therefore, they are only
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::861f1e74b26c3021ba99b0576eebd142
https://vbn.aau.dk/ws/files/295888299/PrewhiteningInfluence_ICASSP_2019.pdf
https://vbn.aau.dk/ws/files/295888299/PrewhiteningInfluence_ICASSP_2019.pdf
Publikováno v:
Nielsen, J K, Kavalekalam, M S, Christensen, M G & Boldt, J B 2018, Model-based Noise PSD Estimation from Speech in Non-stationary Noise . in IEEE International Conference on Acoustics, Speech, and Signal Processing ., 8461683, IEEE, Calgary, Canada, I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, pp. 5424-5428, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Alberta, Canada, 15/04/2018 . https://doi.org/10.1109/ICASSP.2018.8461683
ICASSP
ICASSP
Most speech enhancement algorithms need an estimate of the noise power spectral density (PSD) to work. In this paper, we introduce a model-based framework for doing noise PSD estimation. The proposed framework allows us to include prior spectral info
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da213d35ea086e58e4d4c59ef14ebefa
https://vbn.aau.dk/ws/files/273970863/master.pdf
https://vbn.aau.dk/ws/files/273970863/master.pdf