aalto1 untyped-item.component.html
Fast Randomization for Distributed Low-Bitrate Coding of Speech and Audio
Loading...
Access rights
openAccess
acceptedVersion
URL
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Authors
Date
Major/Subject
Mcode
Degree programme
Language
en
Pages
11
Series
IEEE/ACM Transactions on Audio Speech and Language Processing, Volume 26, issue 1, pp. 19-30
Abstract
Efficient coding of speech and audio in a distributed system requires that quantization errors across nodes are uncorrelated. Yet with conventional methods at low bitrates, quantization levels become increasingly sparse, which does not correspond to the distribution of the input signal and importantly, also reduces coding efficiency in a distributed system. We have recently proposed a distributed speech and audio codec design which applies quantization in a randomized domain such that quantization errors are randomly rotated in the output domain. Similar to dithering, this ensures that quantization errors across nodes are uncorrelated and coding efficiency is retained. In this paper we improve this approach by proposing faster randomization methods, with a computational complexity O(N log N). Presented experiments demonstrate that the proposed randomizations yield uncorrelated signals, that perceptual quality is competitive and that the complexity of the proposed methods is feasible for practical applications.
Description
Other note
Citation
Backstrom, T & Fischer, J 2018, 'Fast Randomization for Distributed Low-Bitrate Coding of Speech and Audio', IEEE/ACM Transactions on Audio Speech and Language Processing, vol. 26, no. 1, pp. 19-30. https://doi.org/10.1109/TASLP.2017.2757601