An Improved Vector Quantisation Algorithm for Speech Transmission Over Noisy Channels

Cawley, Gavin C. ORCID: (1996) An Improved Vector Quantisation Algorithm for Speech Transmission Over Noisy Channels. In: International Conference on Spoken Language Processing (ICSLP-96), 1996-10-01.

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Vector quantisation (VQ) is a method widely used in low bit-rate coding and transmission of speech signals. Unfortunately, a single bit error in the transmitted index, due to noise in the transmission channel, could degrade perceived speech quality at the receiver quite dramatically as the reference vector retrieved by the corrupted index may differ greatly from the vector corresponding to the intended index. The index assignment (IA) process (an NP-complete combinatorial optimisation problem) attempts to reorder the code book to minimise the effects of single-bit errors, but generally only at considerable computational expense. The paper presents an improved vector quantisation algorithm, based on Kohonen's self-organising feature map (K-SOFM), that jointly optimises the quantization error and resistance to noise in the transmission channel. This is achieved using a neighbourhood function based on the Hamming distance between code book indices, rather than the normal Euclidean distance across a two dimensional feature map. As a result, similar reference vectors are recalled by indices with similar binary patterns, minimising the effect of errors in the transmitted index introduced by noise in the transmission channel.

Item Type: Conference or Workshop Item (Other)
Faculty \ School: Faculty of Science > School of Computing Sciences

University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Machine learning in computational biology
Depositing User: EPrints Services
Date Deposited: 01 Oct 2010 13:42
Last Modified: 15 Dec 2022 01:08
DOI: 10.1109/ICSLP.1996.607112

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