An 64-80-96 kbit/s scalable wideband speech coding candidate for ITU-T G.711-WB standardization

Kovesi, B.; Ragot, S.; Guyader, Alain Le

doi:10.1109/icassp.2008.4518731

Cited by 2 publications

(6 citation statements)

References 6 publications

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“…Using condition (34) and expressions (11), (13) and (27), the optimal value for x max is found. For some values of N g , optimal values for x max are given in Table 1.…”

Section: Forward Adaptive Logarithmic Quantizermentioning

confidence: 99%

“…Using (13) we can obtain that g = 10 α/20 (26) Gain g passes through quantizer Q gain witch has N g levels, and the quantized gainĝ is obtained. g i , i = 0, .…”

Section: Forward Adaptive Logarithmic Quantizermentioning

confidence: 99%

“…Without loosing generality, we choose σ 2 0 = 1. From (12), it follows that σ = σ 0 10 α/20 (13) Now, the quantizer used in G.711 codec will be considered. The parameters for this quantizer are μ = 255 and N = 256.…”

Section: μ-Law Logarithmic Quantizermentioning

confidence: 99%

“…The G.711.1 standard should be compatible with G.711 standard, and should also have a little additional delay and hardware. A vast amount of research is done and many solutions are proposed [11][12][13][14]. Our solutions fulfill all stated requirements, so they can be implemented in the low-frequency part of that extended standard (from 0 to 4 kHz).…”

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confidence: 98%

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Forward Adaptive Logarithmic Quantizer with New Lossless Coding Method for Laplacian Source

Perić

Dincic

Denić

et al. 2010

Wireless Pers Commun

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The aim of this paper is to improve the G.711 standard, which is widely used, especially in the public switched telephone network (PSTN). Two solutions are proposed. The first solution uses only lossless coder, achieving a bit-rate decrease of 0.82 bits/sample, compared to the G.711 codec. The second solution uses forward adaptation and a lossless coder, further decreasing the bit-rate (by 1.25 bits/sample) and achieving higher average signal-to-quantization noise ratio (SQNR) in comparison with the G.711 codec. Also, the second solution is more robust than the G.711 codec, which means that it has near constant SQNR for a wide range of input signal power. That is very important for signals whose input power varies with time, such as speech and video signals. Our solutions are compatible with the G.711 codec, they have little additional complexity and delay and therefore can be applied in real-time systems, such as PSTN or VoIP. They can also be used in many other systems, such as WiMax and OFDM, as a replacement or improvement of the G.711 codec. Standardization process of the G.711.1 standard (which is a wide-band extension of the G.711 standard) is largely present. Our solutions fulfill all the requirements for that new standard; therefore they can be implemented in its low-frequency part.

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“…Using condition (34) and expressions (11), (13) and (27), the optimal value for x max is found. For some values of N g , optimal values for x max are given in Table 1.…”

Section: Forward Adaptive Logarithmic Quantizermentioning

confidence: 99%

“…Using (13) we can obtain that g = 10 α/20 (26) Gain g passes through quantizer Q gain witch has N g levels, and the quantized gainĝ is obtained. g i , i = 0, .…”

Section: Forward Adaptive Logarithmic Quantizermentioning

confidence: 99%

Section: μ-Law Logarithmic Quantizermentioning

confidence: 99%

mentioning

confidence: 98%

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Forward Adaptive Logarithmic Quantizer with New Lossless Coding Method for Laplacian Source

Perić

Dincic

Denić

et al. 2010

Wireless Pers Commun

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“…In Ref. [11], the wide-band input signal is also split in two bands. The low band is coded by a low-complexity embedded G.711 coder at 8--10 bits/sample, including noise feedback at the encoder and post-filtering at the decoder.…”

Section: Introductionmentioning

confidence: 99%

Radial compression function for vector quantizer of Laplacian source with high dynamic variance range

Perić

Jovanović

2010

Trans Emerging Tel Tech

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In this paper, our aim is to define a high dynamic range vector quantization model for an i.i.d. Laplacian source. In order to do this we use a geometric approach and lattice quantization. As a result, we achieve symmetry in distribution of code vectors and introduce the radial scalar compression function for lattice cell side determination. This enables derivation of a sophisticated creation for a condition which the radial compression function should satisfy in order to make the SQNR nondependent on variance. It is interesting that the obtained solution represents the generalisation of solution in the case of high dynamic range scalar quantization. Because of that, in the second part of the paper, the well-known semilogarithmic A-law compression characteristic is utilized as radial scalar compression function of geometric vector quantizer. It is shown that such a model has very good performances over a very wide variance range. The proper choice of compression parameter A and dimension n enables the constant SQNR to sustain over much wider variance range than in case of log-scalar quantization. Particularly, the high dimension makes it possible to broaden the variance range over which SQNR remains constant by increasing the A value simultaneously holding the SQNR level unchanged. In comparison with the widely used log-scalar quantization, the presented solution for dimensions from 10 to 140 gives a quality improvement of 7--9 dB, while comparison of maximal SQNR value to that of optimal scalar quantization shows the SQNR growth of 3--5 dB. Furthermore, for dimension 40 the SQNR maximum is only for 0.5 dB lower than that of optimal vector quantization, while dynamic range characteristic broadening is considerable. The cited benefits of high dynamic range vector quantization make it possible to realize a high quality signal compression. Besides, in comparison with the adaptive quantization, our proposal has a smaller implementation complexity.

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An 64-80-96 kbit/s scalable wideband speech coding candidate for ITU-T G.711-WB standardization

Cited by 2 publications

References 6 publications

Forward Adaptive Logarithmic Quantizer with New Lossless Coding Method for Laplacian Source

Forward Adaptive Logarithmic Quantizer with New Lossless Coding Method for Laplacian Source

Radial compression function for vector quantizer of Laplacian source with high dynamic variance range

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