A neural network for blind identification of speech transmission index

Li, FF ORCID: https://orcid.org/0000-0001-9053-963X and Cox, TJ ORCID: https://orcid.org/0000-0002-4075-7564 2003, 'A neural network for blind identification of speech transmission index' , Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on (Volume:2 ), 2 , II-757.

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Abstract

A hybrid neural network model is proposed to determine the speech transmission index of a transmission channel from transmitted speech signals without resort to prior knowledge of original speech. It comprises a Hilbert transform pre-processor, a PCA network for speech feature extraction and a multilayer back-propagation network for nonlinear mapping and case generalization. The developed method utilizes naturally occurring speech signals as probe stimuli, reduces measurement channels from two to one and hence facilitates speech transmission channel assessments under in-use conditions.

Item Type:	Article
Schools:	Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title:	Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on (Volume:2 )
Publisher:	IEEE
ISSN:	1520-6149
Related URLs:	Publication
Funders:	MMU
Depositing User:	Dr Francis F. Li
Date Deposited:	11 May 2016 14:12
Last Modified:	15 Feb 2022 20:47
URI:	https://usir.salford.ac.uk/id/eprint/38940

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