An analysis of cepstral-time feature matrices for noise and channel robust speech recognition

Milner, Ben and Vaseghi, Saeed V. (1995) An analysis of cepstral-time feature matrices for noise and channel robust speech recognition. In: Proc. 4th European Conference on Speech Communication and Technology. UNSPECIFIED.

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Abstract

This paper presents an analysis of the cepstral-time matrix. The coefficients of the cepstral-time matrix are found to be similar to the standard cepstral vector with differential features augmented on. It is also shown that the cepstral-time matrix is inherently robust to convolutional channel distortion. Spectral-subtraction, Wiener filtering and model combination are extended into two-dimensions where improved noise robustness is achieved. Experimental results using the NOISEX database with noise and channel distorted speech are presented.,

Item Type: Book Section
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Interactive Graphics and Audio
Faculty of Science > Research Groups > Smart Emerging Technologies
Faculty of Science > Research Groups > Data Science and AI
Depositing User: LivePure Connector
Date Deposited: 09 Jan 2024 01:20
Last Modified: 10 Dec 2024 01:13
URI: https://ueaeprints.uea.ac.uk/id/eprint/94106
DOI: 10.21437/Eurospeech.1995-138

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