On Optimal Filtering for Speech Decomposition

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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.
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Detaljer

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
Titel26th European Signal Processing Conference (EUSIPCO)
Publikationsdato18 maj 2018
StatusAccepteret/In press - 18 maj 2018
PublikationsartForskning
Peer reviewJa
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
NavnProceedings of the European Signal Processing Conference
ISSN2076-1465

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