Fast Randomization for Distributed Low-Bitrate Coding of Speech and Audio

Research output: Contribution to journalArticleScientificpeer-review


Research units

  • Friedrich-Alexander University Erlangen-Nürnberg


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.


Original languageEnglish
Pages (from-to)19-30
Number of pages11
JournalIEEE/ACM Transactions on Audio Speech and Language Processing
Issue number1
Publication statusPublished - Jan 2018
MoE publication typeA1 Journal article-refereed

    Research areas

  • audio coding, Codecs, Complexity theory, distributed coding, orthonormal matrix, Quantization (signal), randomization, Speech, Speech coding, speech coding, Speech processing, superfast algorithm

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