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Acoustic models for online blind source dereverberation using sequential Monte Carlo methods

Acoustic models for online blind source dereverberation using sequential Monte Carlo methods
Acoustic models for online blind source dereverberation using sequential Monte Carlo methods

Reverberation and noise cause significant deterioration of audio quality and intelligibility to signals recorded in acoustic environments. Noise is usually modeled as a common signal observed in the room and independent of room acoustics. However, this simplistic model cannot necessarily capture the effects of separate noise sources at different locations in the room. This paper proposes a noise model that considers distinct noise sources whose individual acoustic impulse responses are separated into source-sensor specific and common acoustical resonances. Further to noise, the signal is distorted by reverberation. Using parametric models of the system, recursive expressions of the filtering distribution can be derived. Based on these results, a sequential Monte Carlo approach for online dereverberation and enhancement is proposed. Simulation results for speech are presented to verify the effectiveness of the model and method.

Acoustic signal processing, Monte Carlo, Speech dereverberation sequential estimation, Speech enhancement
1520-6149
4597-4600
IEEE
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Hopgood, James R.
ae180a4d-33bf-468d-ab66-5eeb152e7fc2
Bell, Judith
1ae45580-f516-4e83-af09-b6a9aa63f0f7
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Hopgood, James R.
ae180a4d-33bf-468d-ab66-5eeb152e7fc2
Bell, Judith
1ae45580-f516-4e83-af09-b6a9aa63f0f7

Evers, Christine, Hopgood, James R. and Bell, Judith (2008) Acoustic models for online blind source dereverberation using sequential Monte Carlo methods. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP. IEEE. pp. 4597-4600 . (doi:10.1109/ICASSP.2008.4518680).

Record type: Conference or Workshop Item (Paper)

Abstract

Reverberation and noise cause significant deterioration of audio quality and intelligibility to signals recorded in acoustic environments. Noise is usually modeled as a common signal observed in the room and independent of room acoustics. However, this simplistic model cannot necessarily capture the effects of separate noise sources at different locations in the room. This paper proposes a noise model that considers distinct noise sources whose individual acoustic impulse responses are separated into source-sensor specific and common acoustical resonances. Further to noise, the signal is distorted by reverberation. Using parametric models of the system, recursive expressions of the filtering distribution can be derived. Based on these results, a sequential Monte Carlo approach for online dereverberation and enhancement is proposed. Simulation results for speech are presented to verify the effectiveness of the model and method.

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More information

Published date: 16 September 2008
Venue - Dates: 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP, , Las Vegas, NV, United States, 2008-03-30 - 2008-04-03
Keywords: Acoustic signal processing, Monte Carlo, Speech dereverberation sequential estimation, Speech enhancement

Identifiers

Local EPrints ID: 445868
URI: http://eprints.soton.ac.uk/id/eprint/445868
ISSN: 1520-6149
PURE UUID: 92be5365-5f96-44cb-8a56-3deabc874884
ORCID for Christine Evers: ORCID iD orcid.org/0000-0003-0757-5504

Catalogue record

Date deposited: 12 Jan 2021 17:32
Last modified: 18 Feb 2021 17:41

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