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Cosine-/Sine-Modulated Filter Banks pp 13–37Cite as

Audio Coding Standards, (Proprietary) Audio Compression Algorithms, and Broadcasting/Speech/Data Communication Codecs: Overview of Adopted Filter Banks

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Abstract

In general, audio coding or audio compression algorithms are used to obtain compact digital representation of high-quality audio signals for their efficient transmission and storage. The central objective in audio coding is to represent the signal with a minimum number of bits while achieving its transparent reproduction. Besides speech coding schemes based on linear prediction methods especially tailored for efficient speech compression, the developed perceptual transform-based audio coding schemes gained a greater attention, particularly for applications in consumer electronics. Typically, any transform-based audio coding scheme utilizes a near-perfect quadrature mirror filter (QMF) and/or perfect reconstruction cosine-modulated filter bank to obtain a block-wise representation of the audio signal in the frequency domain. Perceptual transform-based audio coding schemes developed up to now are briefly reviewed including the family of ISO/IEC MPEG audio coding standards, proprietary audio compression algorithms, broadcasting/speech/data communication codecs, as well as open-free, patent royalty-free audio/speech codecs. The discussion is concentrated especially on adopted near-perfect QMF and perfect reconstruction cosine-modulated filter banks, processing methods, and specified transform block sizes.

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Authors and Affiliations

  1. Institute of Informatics, Slovak Academy of Sciences, Bratislava, Slovakia

    Vladimir Britanak

  2. The University of Texas at Arlington, Arlington, TX, USA

    K. R. Rao

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  1. Vladimir Britanak
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Britanak, V., Rao, K.R. (2018). Audio Coding Standards, (Proprietary) Audio Compression Algorithms, and Broadcasting/Speech/Data Communication Codecs: Overview of Adopted Filter Banks. In: Cosine-/Sine-Modulated Filter Banks. Springer, Cham. https://doi.org/10.1007/978-3-319-61080-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-61080-1_2

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