A neural network for blind identification of speech transmission index

Li, FF; Cox, TJ

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.

Citation

Li, F., & Cox, T. (2003). A neural network for blind identification of speech transmission index. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing, 2, II-757. https://doi.org/10.1109/ICASSP.2003.1202477

• Journal Article Type: Article
• Conference Name: Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
• Start Date: Apr 6, 2003
• End Date: Apr 10, 2003
• Publication Date: Jan 1, 2003
• Deposit Date: May 11, 2016
• Journal: Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on (Volume:2 )
• Print ISSN: 1520-6149
• Publisher: Institute of Electrical and Electronics Engineers
• Volume: 2
• Pages: II-757
• Book Title: 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).
• DOI: https://doi.org/10.1109/ICASSP.2003.1202477
• Publisher URL: http://dx.doi.org/10.1109/ICASSP.2003.1202477
• Related Public URLs: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8535
• Additional Information: Event Type : Conference; Funders : MMU