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Compressive speech enhancement in the modulation domain

Compressive speech enhancement in the modulation domain
Compressive speech enhancement in the modulation domain
Compressive speech enhancement (CSE) has gained popularity in recent years as it bypasses the need for noise estimation. Parallel to that, modulation domain has been widely studied in speech applications as it offers a more compact representation and is closely associated with speech intelligibility enhancement. Motivated by the development in modulation domain and CSE, this paper seeks to explore the suitability of modulation domain based sparse reconstruction for use in CSE. The main idea is to study if the increased sparsity in the modulation domain would benefit sparse reconstruction in CSE. The findings reveal that modulation transformation is sparser and offers a stronger restricted isometry property (RIP) compared to the frequency transformation, which is essential for sparse recovery with a high probability. The results are then extended to show that the sparse reconstruction error in the modulation domain is upper bounded by the frequency domain. Experimental results in a CSE setting concur with the theoretical derivations, with modulation domain CSE outperforming the frequency domain CSE through different speech quality measures.
0167-6393
87-99
Low, Siow Yong
d101f0b9-404e-4e2a-bb4f-a605f0811108
Low, Siow Yong
d101f0b9-404e-4e2a-bb4f-a605f0811108

Low, Siow Yong (2018) Compressive speech enhancement in the modulation domain. Speech Communication, 87-99. (doi:10.1016/j.specom.2018.08.003).

Record type: Article

Abstract

Compressive speech enhancement (CSE) has gained popularity in recent years as it bypasses the need for noise estimation. Parallel to that, modulation domain has been widely studied in speech applications as it offers a more compact representation and is closely associated with speech intelligibility enhancement. Motivated by the development in modulation domain and CSE, this paper seeks to explore the suitability of modulation domain based sparse reconstruction for use in CSE. The main idea is to study if the increased sparsity in the modulation domain would benefit sparse reconstruction in CSE. The findings reveal that modulation transformation is sparser and offers a stronger restricted isometry property (RIP) compared to the frequency transformation, which is essential for sparse recovery with a high probability. The results are then extended to show that the sparse reconstruction error in the modulation domain is upper bounded by the frequency domain. Experimental results in a CSE setting concur with the theoretical derivations, with modulation domain CSE outperforming the frequency domain CSE through different speech quality measures.

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More information

Accepted/In Press date: 5 August 2018
e-pub ahead of print date: 7 August 2018
Published date: September 2018

Identifiers

Local EPrints ID: 424588
URI: http://eprints.soton.ac.uk/id/eprint/424588
ISSN: 0167-6393
PURE UUID: 71c88f06-00d5-4c82-b0b6-77cf6e2aa5e2

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Date deposited: 05 Oct 2018 11:39
Last modified: 15 Mar 2024 21:22

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Contributors

Author: Siow Yong Low

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