Golomb-rice coding optimized via LPC for frequency domain audio coder

Abstract

We have devised a method to optimize Golomb-Rice coding of frequency spectra, aiming at its use in frequency domain audio coder, using spectral envelopes extracted by linear predictive coding (LPC) from amplitude spectra instead of conventional power spectra according to theoretical investigations. This optimization improves the efficiency of the Golomb-Rice coding by allocating Rice parameter at each frequency bin based on the value of the envelopes, resulting in the enhancement of the objective and subjective quality of the state-of-the-art wideband coder at 16 kbit/s. Therefore, the method introduced here is expected to be useful for coding audio signals at low-bit-rate and low-delay conditions, required in mobile communications.

Optimal Coding of Generalized-Gaussian-Distributed Frequency Spectra for Low-Delay Audio Coder With Powered All-Pole Spectrum Estimation

“…(11) and (17) as (18) which matches the conventional LP. Additionally, when the shape parameter takes , meaning a Laplacian, the extraction of the envelope from the input is the same as the one in our previous study on optimizing Golomb-Rice coding [31].…”

Progress in LPC-based frequency-domain audio coding

“…We therefore call this method powered all-pole spectrum estimation (PAPSE). Note that PAPSE becomes equivalent to LPC when α = 2 and to [10] when α = 1.…”

“…The second is frequency-resolution warping of the LPC envelope [8,9]. The third is powered all-pole spectrum estimation (PAPSE) [10,11], for LPC modeling of the envelope, which takes the distribution of quantized MDCT coefficients into account. All tools are intended to enhance the efficiency of entropy coding of quantized MDCT coefficients.…”

Order adaptive Golomb rice coding for high variability sources

“…The use of contexts has been proposed for Golomb codes optimization in [11]. In [12] the authors have proposed to use the LPC spectral envelope for the adaptation of the Golomb Rice parameter at each frequency bin for a frequency domain audio encoder.…”

“…The artificial counts vector is generated such that its corresponding mapping gives an almost symmetric distribution with the maximum in the centre. The articifial counts vector is given by: h = [1, 3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,30,28,26,24,22,20,18,16,14,12,10,8,6,4,2].…”