A linear predictive coding apparatus includes: a linear predictive analysis part performing linear predictive analysis using a pseudo correlation function signal sequence obtained by performing inverse Fourier transform regarding the .sub.1-th power of absolute values of the frequency domain sample sequence corresponding to the time-series signal as a power spectrum to obtain coefficients transformable to linear predictive coefficients; an adaptation part adapting values for a plurality of plural candidates for coefficients transformable to linear predictive coefficients stored in a code book in a code book storing part and the coefficients transformable to linear predictive coefficients obtained by the linear predictive analysis part; and a coding part obtaining a linear predictive coefficient code corresponding to the coefficients transformable to linear predictive coefficients, using the plurality of candidates for coefficients transformable to linear predictive coefficients and the coefficients transformable to linear predictive coefficients for which the values of have been adapted.

A schematic block diagram of an audio encoder for encoding a multichannel audio signal is shown. The audio encoder includes a linear prediction domain encoder, a frequency domain encoder, and a controller for switching between the linear prediction domain encoder and the frequency domain encoder. The controller is configured such that a portion of the multichannel signal is represented either by an encoded frame of the linear prediction domain encoder or by an encoded frame of the frequency domain encoder. The linear prediction domain encoder includes a downmixer for downmixing the multichannel signal to obtain a downmixed signal. The linear prediction domain encoder further includes a linear prediction domain core encoder for encoding the downmix signal and furthermore, the linear prediction domain encoder includes a first joint multichannel encoder for generating first multichannel information from the multichannel signal.

A schematic block diagram of an audio encoder for encoding a multichannel audio signal is shown. The audio encoder includes a linear prediction domain encoder, a frequency domain encoder, and a controller for switching between the linear prediction domain encoder and the frequency domain encoder. The controller is configured such that a portion of the multichannel signal is represented either by an encoded frame of the linear prediction domain encoder or by an encoded frame of the frequency domain encoder. The linear prediction domain encoder includes a downmixer for downmixing the multichannel signal to obtain a downmixed signal. The linear prediction domain encoder further includes a linear prediction domain core encoder for encoding the downmix signal and furthermore, the linear prediction domain encoder includes a first joint multichannel encoder for generating first multichannel information from the multichannel signal.

An encoding method, a decoding method, an encoder for performing the encoding method, and a decoder for performing the decoding method are provided. The encoding method includes outputting LP coefficients bitstream and a residual signal by performing an LP analysis on an input signal, outputting a first latent signal obtained by encoding a periodic component of the residual signal, a second latent signal obtained by encoding a non-periodic component of the residual signal, and a weight vector for each of the first latent signal and the second latent signal, using a first neural network module, and outputting a first bitstream obtained by quantizing the first latent signal, a second bitstream obtained by quantizing the second latent signal, and a weight bitstream obtained by quantizing the weight vector, using a quantization module.

An encoding method, a decoding method, an encoder for performing the encoding method, and a decoder for performing the decoding method are provided. The encoding method includes outputting LP coefficients bitstream and a residual signal by performing an LP analysis on an input signal, outputting a first latent signal obtained by encoding a periodic component of the residual signal, a second latent signal obtained by encoding a non-periodic component of the residual signal, and a weight vector for each of the first latent signal and the second latent signal, using a first neural network module, and outputting a first bitstream obtained by quantizing the first latent signal, a second bitstream obtained by quantizing the second latent signal, and a weight bitstream obtained by quantizing the weight vector, using a quantization module.