Finite-state entropy-constrained vector quantiser for audio modified discrete cosine transform coefficients uniform quantisation

Finite-state entropy-constrained vector quantiser for audio modified discrete cosine transform coefficients uniform quantisation

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In this paper, an entropy-constrained vector quantiser (ECVQ) scheme with finite memory, called finite-state ECVQ (FS-ECVQ), is presented. This scheme consists of a finite-state vector quantiser (FSVQ) and multiple component ECVQs. By utilising the FSVQ, the inter-frame dependencies within source sequence can be effectively exploited and no side information needs to be transmitted. By employing the ECVQs, the total memory requirements of FS-ECVQ can be efficiently decreased while the coding performance is improved. An FS-ECVQ, designed for the modified discrete cosine transform coefficients coding, was implemented and evaluated based on the unified speech and audio coding (USAC) scheme. Results showed that the FS-ECVQ achieved reduction of the total memory requirements by 92.3%, compared with the encoder in USAC working draft 6 (WD6), and over 10%, compared with the encoder in USAC final version (FINAL), while maintaining coding performance similar to FINAL, which was about 4% better than that of WD6.


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