Abstract
Modern speech coders necessitate efficient coding of the linear predictive coding (LPC) coefficients. Line spectral Frequencies (LSF) and Immittance Spectral Frequencies (ISF) parameters are currently the most efficient choices of transmission parameters for the LPC coefficients. In this paper, we present a voicing-based classified split vector quantization scheme developed for efficient coding of wideband AMR-WB G.722.2 ISF (Immittance Spectral Frequencies) parameters under noiseless channel conditions. It was designed based on the classified vector quantization (CVQ) structure combined with the split vector quantization (SVQ). Simulation results will show that the new ISF coding scheme, called ISF-CSVQ coder, performs better than the conventional non classified ISF-SVQ, while saving several bits per frame.
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Bouzid, M., Cheraitia, SE. (2015). Voicing-Based Classified Split Vector Quantizer for Efficient Coding of AMR-WB ISF Parameters. In: Ronzhin, A., Potapova, R., Fakotakis, N. (eds) Speech and Computer. SPECOM 2015. Lecture Notes in Computer Science(), vol 9319. Springer, Cham. https://doi.org/10.1007/978-3-319-23132-7_58
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DOI: https://doi.org/10.1007/978-3-319-23132-7_58
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