A method for partitioning of input vectors for coding is presented. The method comprises obtaining of an input vector. The input vector is segmented, in a non-recursive manner, into an integer number, N.sup.SEG, of input vector segments. A representation of a respective relative energy difference between parts of the input vector on each side of each boundary between the input vector segments is determined, in a recursive manner. The input vector segments and the representations of the relative energy differences are provided for individual coding. Partitioning units and computer programs for partitioning of input vectors for coding, as well as positional encoders, are presented.

Efficient assignment of bit numbers is performed even under a low bit rate condition. A quantizer 12 obtains a quantized spectral sequence from a frequency spectral sequence. An integer transformer 13 obtains a unified quantized spectral sequence by obtaining, by a bijective transformation, a transformed integer for each of the sets, each being made up of integer values, obtained from the quantized spectral sequence. An integer encoder 15 obtains an integer code by encoding the unified quantized spectral sequence using a bit assignment sequence. An object-to-be-encoded estimator 18 obtains an estimated unified spectral sequence from the frequency spectral sequence by a transformation which is performed by the integer transformer 13 or a transformation that approximates the magnitude relationship between values before and after the above transformation. A bit assigner 14 obtains a bit assignment sequence and a bit assignment code from the estimated unified spectral sequence. A quantization step size obtainer 11 obtains a quantization step size from the estimated unified spectral sequence and the bit assignment sequence.

Disclosed are methods of encoding and decoding an audio signal, and an encoder and a decoder for performing the methods. The method of encoding an audio signal includes identifying an input signal corresponding to a low frequency band of the audio signal, windowing the input signal, generating a first latent vector by inputting the windowed input signal to a first encoding model, transforming the windowed input signal into a frequency domain, generating a second latent vector by inputting the transformed input signal to a second encoding model, generating a final latent vector by combining the first latent vector and the second latent vector, and generating a bitstream corresponding to the final latent vector.

Disclosed are methods of encoding and decoding an audio signal, and an encoder and a decoder for performing the methods. The method of encoding an audio signal includes identifying an input signal corresponding to a low frequency band of the audio signal, windowing the input signal, generating a first latent vector by inputting the windowed input signal to a first encoding model, transforming the windowed input signal into a frequency domain, generating a second latent vector by inputting the transformed input signal to a second encoding model, generating a final latent vector by combining the first latent vector and the second latent vector, and generating a bitstream corresponding to the final latent vector.

An information encoder for encoding an information signal includes: a converter for converting the linear prediction coefficients of the predictive polynomial A(z) to frequency values f.sub.1 . . . f.sub.n of a spectral frequency representation of the predictive polynomial A(z), wherein the converter is configured to determine the frequency values f.sub.1 . . . f.sub.n by analyzing a pair of polynomials P(z) and Q(z) being defined as $P\left(z\right)=A\left(z\right)+z^{-m-l}A\left(z^{-1}\right)\mathrm{and}$$Q\left(z\right)=A\left(z\right)-z^{-m-l}A\left(z^{-1}\right),$
wherein m is

An information encoder for encoding an information signal includes: a converter for converting the linear prediction coefficients of the predictive polynomial A(z) to frequency values f.sub.1 . . . f.sub.n of a spectral frequency representation of the predictive polynomial A(z), wherein the converter is configured to determine the frequency values f.sub.1 . . . f.sub.n by analyzing a pair of polynomials P(z) and Q(z) being defined as $P\left(z\right)=A\left(z\right)+z^{-m-l}A\left(z^{-1}\right)\mathrm{and}$$Q\left(z\right)=A\left(z\right)-z^{-m-l}A\left(z^{-1}\right),$
wherein m is

Audio decoder for decoding an encoded audio signal having multi-channel audio data having data for two or more audio channels, and information on jointly encoded scale parameters, having: a scale parameter decoder for decoding the information on the jointly encoded scale parameters to obtain a first and a second set of scale parameters for a first channel and a second channel, respectively, of a decoded audio signal; and a signal processor for applying the first and second sets of scale parameters to a first and second channel representation, respectively, derived from the multi-channel audio data to obtain the first and second channels of the decoded audio signal, wherein the jointly encoded scale parameters have information on a first group and on a second group of jointly encoded scale parameters, and wherein the scale parameter decoder is configured to combine a jointly encoded scale parameter of the first group and one of the second group using a first and a second combination rule, respectively, to obtain a scale parameter of the first and second sets of scale parameters.

In general, techniques are described for coding of vectors decomposed from higher order ambisonic coefficients. A device comprising a processor and a memory may perform the techniques. The processor may be configured to obtain from a bitstream data indicative of a plurality of weight values that represent a vector that is included in a decomposed version of the plurality of HOA coefficients. Each of the weight values may correspond to a respective one of a plurality of weights in a weighted sum of code vectors that represents the vector and that includes a set of code vectors. The processor may further be configured to reconstruct the vector based on the weight values and the code vectors. The memory may be configured to store the reconstructed vector.

In general, techniques are described for coding of vectors decomposed from higher order ambisonic coefficients. A device comprising a processor and a memory may perform the techniques. The processor may be configured to obtain from a bitstream data indicative of a plurality of weight values that represent a vector that is included in a decomposed version of the plurality of HOA coefficients. Each of the weight values may correspond to a respective one of a plurality of weights in a weighted sum of code vectors that represents the vector and that includes a set of code vectors. The processor may further be configured to reconstruct the vector based on the weight values and the code vectors. The memory may be configured to store the reconstructed vector.

An audio quantizer for quantizing a plurality of audio information items has: a first stage vector quantizer for quantizing the plurality of audio information items to determine a first stage vector quantization result and a plurality of intermediate quantized items corresponding to the first stage vector quantization result; a residual item determiner for calculating a plurality of residual items from the plurality of intermediate quantized items and the plurality of audio information items; and a second stage vector quantizer for quantizing the plurality of residual items to obtain a second stage vector quantization result, wherein the first stage vector quantization result and the second stage vector quantization result are a quantized representation of the plurality of audio information items.