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Block-based TVAR models for single-channel blind dereverberation of speech from a moving speaker

Block-based TVAR models for single-channel blind dereverberation of speech from a moving speaker
Block-based TVAR models for single-channel blind dereverberation of speech from a moving speaker

In reverberant environments, a moving speaker yields a dynamically changing source-sensor geometry giving rise to a spatially-varying acoustic impulse response (AIR) between the source and sensor. Consequently, this leads to a time-varying convolutional relationship between the source signal and the observations and thus spectral colouration of the received signal. It is therefore desirable to reduce the effect of reverberation. In this paper, a model-based approach is proposed for single-channel blind dereverberation of speech from a moving speaker acquired in an acoustic environment. The sound source is modelled by a block-based time-varying AR (TVAR) process, and the channel by a linear time-varying all-pole filter. In each case, the AR parameters are represented as a linear combination of known basis functions with unknown weightings. The speech model captures local nonstationarity while taking account of the global nonstationary characteristics inherent in long segments of speech. As an initial step towards single-channel blind dereverberation of real speech signals, this paper presents simulation results for synthetic data to demonstrate the algorithm developed.

274-278
IEEE
Hopgood, James R.
ae180a4d-33bf-468d-ab66-5eeb152e7fc2
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b
Hopgood, James R.
ae180a4d-33bf-468d-ab66-5eeb152e7fc2
Evers, Christine
93090c84-e984-4cc3-9363-fbf3f3639c4b

Hopgood, James R. and Evers, Christine (2007) Block-based TVAR models for single-channel blind dereverberation of speech from a moving speaker. In IEEE Workshop on Statistical Signal Processing, SSP. IEEE. pp. 274-278 . (doi:10.1109/SSP.2007.4301262).

Record type: Conference or Workshop Item (Paper)

Abstract

In reverberant environments, a moving speaker yields a dynamically changing source-sensor geometry giving rise to a spatially-varying acoustic impulse response (AIR) between the source and sensor. Consequently, this leads to a time-varying convolutional relationship between the source signal and the observations and thus spectral colouration of the received signal. It is therefore desirable to reduce the effect of reverberation. In this paper, a model-based approach is proposed for single-channel blind dereverberation of speech from a moving speaker acquired in an acoustic environment. The sound source is modelled by a block-based time-varying AR (TVAR) process, and the channel by a linear time-varying all-pole filter. In each case, the AR parameters are represented as a linear combination of known basis functions with unknown weightings. The speech model captures local nonstationarity while taking account of the global nonstationary characteristics inherent in long segments of speech. As an initial step towards single-channel blind dereverberation of real speech signals, this paper presents simulation results for synthetic data to demonstrate the algorithm developed.

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More information

Published date: 1 December 2007
Venue - Dates: 2007 IEEE/SP 14th WorkShoP on Statistical Signal Processing, SSP 2007, , Madison, WI, United States, 2007-08-25 - 2007-08-28

Identifiers

Local EPrints ID: 445865
URI: http://eprints.soton.ac.uk/id/eprint/445865
PURE UUID: cbe2aecb-5e1c-451a-815d-4fce4e7a8de5
ORCID for Christine Evers: ORCID iD orcid.org/0000-0003-0757-5504

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Date deposited: 12 Jan 2021 17:32
Last modified: 12 Jan 2021 17:32

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Contributors

Author: James R. Hopgood
Author: Christine Evers ORCID iD

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