A linear prediction coding (LPC) parameter coding method is provided. The method includes: determining a reference LPC parameter from a plurality of LPC parameters, performing direct coding on the reference LPC parameter, and performing reference coding on a non-reference LPC parameter based on the determined LPC parameter. The method includes: obtaining a direct coding result of the reference LPC parameter and determining a residual coding result of the non-reference LPC parameter.

A linear prediction coding (LPC) parameter coding method is provided. The method includes: determining a reference LPC parameter from a plurality of LPC parameters, performing direct coding on the reference LPC parameter, and performing reference coding on a non-reference LPC parameter based on the determined LPC parameter. The method includes: obtaining a direct coding result of the reference LPC parameter and determining a residual coding result of the non-reference LPC parameter.

Provided is an encoding method according to various example embodiments and an encoder performing the method. The encoding method includes outputting a linear prediction(LP) coefficients bitstream and a residual signal by performing a linear prediction analysis on an input signal, outputting a first latent signal obtained by encoding a periodic component of the residual signal, using a first neural network module, outputting a first bitstream obtained by quantizing the first latent signal, using a quantization module, outputting a second latent signal obtained by encoding an aperiodic component of the residual signal, using the first neural network module, and outputting a second bitstream obtained by quantizing the second latent signal, using the quantization module, wherein the aperiodic component of the residual signal is calculated based on a periodic component of the residual signal decoded from the quantized first latent signal output by de-quantizing the first bitstream.

An apparatus for selecting one of a first encoding algorithm having a first characteristic and a second encoding algorithm having a second characteristic for encoding a portion of an audio signal to obtain an encoded version of the portion of the audio signal has a first estimator for estimating a first quality measure for the portion of the audio signal, which is associated with the first encoding algorithm, without actually encoding and decoding the portion of the audio signal using the first encoding algorithm. A second estimator is provided for estimating a second quality measure for the portion of the audio signal, which is associated with the second encoding algorithm, without actually encoding and decoding the portion of the audio signal using the second encoding algorithm. The apparatus has a controller for selecting the first or second encoding algorithms based on a comparison between the first and second quality measures.

The invention provides an audio encoder including a combination of a linear predictive coding filter having a plurality of linear predictive coding coefficients and a time-frequency converter, wherein the combination is configured to filter and to convert a frame of the audio signal into a frequency domain in order to output a spectrum based on the frame and on the linear predictive coding coefficients; a low frequency emphasizer configured to calculate a processed spectrum based on the spectrum, wherein spectral lines of the processed spectrum representing a lower frequency than a reference spectral line are emphasized; and a control device configured to control the calculation of the processed spectrum by the low frequency emphasizer depending on the linear predictive coding coefficients of the linear predictive coding filter.

The invention provides an audio encoder including a combination of a linear predictive coding filter having a plurality of linear predictive coding coefficients and a time-frequency converter, wherein the combination is configured to filter and to convert a frame of the audio signal into a frequency domain in order to output a spectrum based on the frame and on the linear predictive coding coefficients; a low frequency emphasizer configured to calculate a processed spectrum based on the spectrum, wherein spectral lines of the processed spectrum representing a lower frequency than a reference spectral line are emphasized; and a control device configured to control the calculation of the processed spectrum by the low frequency emphasizer depending on the linear predictive coding coefficients of the linear predictive coding filter.

An audio codec suitable for robust wireless transmission of high quality audio with low latency, still at a moderate bit rate. The encoding and decoding methods are based on ADPCM and in addition to the encoded output bits APM, additional data QB are included in output data blocks, namely data QB representing an internal value of the adaptive quantization ADQ of the ADPCM encoding algorithm, especially a scaling factor encoded and truncated to such as 8 bits. Further, output data blocks preferably include data CFB representing an internal value of the predictor PR of the ADPCM encoding algorithm, especially data CFB representing coefficients of a lattice prediction FIR filter which, truncated to such as 8 bits, can be sequentially included in output data blocks. These additional data QB, CFB regarding internal values of the ADPCM encoding algorithm can be utilized at the encoder side to increase robustness against loss of data blocks in wireless transmission. Especially, the decoding algorithm may comprise comparing its current internal ADPCM decoding values corresponding to the received internal values QB, CFB from the encoder, and in case there is a difference, the decoder can adapt or overwrite its internal values to the ones received QB, CFB. This helps to ensure fast recovery after lost data blocks, thereby ensuring robustness against artefacts in the reconstructed signal, e.g. clicks in case of audio.

An audio codec suitable for robust wireless transmission of high quality audio with low latency, still at a moderate bit rate. The encoding and decoding methods are based on ADPCM and in addition to the encoded output bits APM, additional data QB are included in output data blocks, namely data QB representing an internal value of the adaptive quantization ADQ of the ADPCM encoding algorithm, especially a scaling factor encoded and truncated to such as 8 bits. Further, output data blocks preferably include data CFB representing an internal value of the predictor PR of the ADPCM encoding algorithm, especially data CFB representing coefficients of a lattice prediction FIR filter which, truncated to such as 8 bits, can be sequentially included in output data blocks. These additional data QB, CFB regarding internal values of the ADPCM encoding algorithm can be utilized at the encoder side to increase robustness against loss of data blocks in wireless transmission. Especially, the decoding algorithm may comprise comparing its current internal ADPCM decoding values corresponding to the received internal values QB, CFB from the encoder, and in case there is a difference, the decoder can adapt or overwrite its internal values to the ones received QB, CFB. This helps to ensure fast recovery after lost data blocks, thereby ensuring robustness against artefacts in the reconstructed signal, e.g. clicks in case of audio.

Disclosed is a method of processing a residual signal for audio coding and an audio coding apparatus. The method learns a feature map of a reference signal through a residual signal learning engine including a convolutional layer and a neural network and performs learning based on a result obtained by mapping a node of an output layer of the neural network and a quantization level of index of the residual signal.

An apparatus including circuitry configured to: obtain a spatial audio signal including at least one audio signal and spatial metadata associated with the at least one audio signal; obtain at least one data set related to binaural rendering; obtain at least one pre-defined data set related to binaural rendering; and generate a binaural audio signal based on a combination of at least part of the at least one data set and the at least one pre-defined data set, and the spatial audio signal.