On Optimal Filtering for Speech Decomposition

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Resumé

Optimal linear filtering has been used extensively for speech enhancement. In this paper, we take a first step in trying to apply linear filtering to the decomposition of a noisy speech signal into its components. The problem of decomposing speech into its voiced and unvoiced components is considered as an estimation problem. Assuming a harmonic model for the voiced speech, we propose a Wiener filtering scheme which estimates both components separately in the presence of noise. It is shown under which conditions this optimal filtering formulation outperforms two state-of-the-art speech decomposition methods, which is also revealed by objective measures, spectrograms and informal listening tests.
OriginalsprogEngelsk
Titel2018 26th European Signal Processing Conference (EUSIPCO)
Antal sider5
ForlagIEEE
Publikationsdato2018
Sider2325-2329
ISBN (Trykt)978-90-827970-0-8, 978-1-5386-3736-4
ISBN (Elektronisk)978-9-0827-9701-5
DOI
StatusUdgivet - 2018
Begivenhed26th European Signal Processing Conference - Rome, Italien
Varighed: 3 sep. 20187 sep. 2018
Konferencens nummer: 26
http://www.eusipco2018.org

Konference

Konference26th European Signal Processing Conference
Nummer26
LandItalien
ByRome
Periode03/09/201807/09/2018
Internetadresse
NavnProc. European Signal Processing Conference
ISSN2076-1465

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Decomposition
Speech enhancement

Citer dette

Esquivel Jaramillo, A., Nielsen, J. K., & Christensen, M. G. (2018). On Optimal Filtering for Speech Decomposition. I 2018 26th European Signal Processing Conference (EUSIPCO) (s. 2325-2329). IEEE. Proc. European Signal Processing Conference https://doi.org/10.23919/EUSIPCO.2018.8553512
Esquivel Jaramillo, Alfredo ; Nielsen, Jesper Kjær ; Christensen, Mads Græsbøll. / On Optimal Filtering for Speech Decomposition. 2018 26th European Signal Processing Conference (EUSIPCO). IEEE, 2018. s. 2325-2329 (Proc. European Signal Processing Conference).
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title = "On Optimal Filtering for Speech Decomposition",
abstract = "Optimal linear filtering has been used extensively for speech enhancement. In this paper, we take a first step in trying to apply linear filtering to the decomposition of a noisy speech signal into its components. The problem of decomposing speech into its voiced and unvoiced components is considered as an estimation problem. Assuming a harmonic model for the voiced speech, we propose a Wiener filtering scheme which estimates both components separately in the presence of noise. It is shown under which conditions this optimal filtering formulation outperforms two state-of-the-art speech decomposition methods, which is also revealed by objective measures, spectrograms and informal listening tests.",
keywords = "speech decomposition, time-domain filtering, Wiener filter, voiced speech, unvoiced speech",
author = "{Esquivel Jaramillo}, Alfredo and Nielsen, {Jesper Kj{\ae}r} and Christensen, {Mads Gr{\ae}sb{\o}ll}",
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Esquivel Jaramillo, A, Nielsen, JK & Christensen, MG 2018, On Optimal Filtering for Speech Decomposition. i 2018 26th European Signal Processing Conference (EUSIPCO). IEEE, Proc. European Signal Processing Conference, s. 2325-2329, Rome, Italien, 03/09/2018. https://doi.org/10.23919/EUSIPCO.2018.8553512

On Optimal Filtering for Speech Decomposition. / Esquivel Jaramillo, Alfredo ; Nielsen, Jesper Kjær; Christensen, Mads Græsbøll.

2018 26th European Signal Processing Conference (EUSIPCO). IEEE, 2018. s. 2325-2329 (Proc. European Signal Processing Conference).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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N2 - Optimal linear filtering has been used extensively for speech enhancement. In this paper, we take a first step in trying to apply linear filtering to the decomposition of a noisy speech signal into its components. The problem of decomposing speech into its voiced and unvoiced components is considered as an estimation problem. Assuming a harmonic model for the voiced speech, we propose a Wiener filtering scheme which estimates both components separately in the presence of noise. It is shown under which conditions this optimal filtering formulation outperforms two state-of-the-art speech decomposition methods, which is also revealed by objective measures, spectrograms and informal listening tests.

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Esquivel Jaramillo A, Nielsen JK, Christensen MG. On Optimal Filtering for Speech Decomposition. I 2018 26th European Signal Processing Conference (EUSIPCO). IEEE. 2018. s. 2325-2329. (Proc. European Signal Processing Conference). https://doi.org/10.23919/EUSIPCO.2018.8553512