A sound signal linear predictive coding apparatus, wherein a parameter η is a positive number; a parameter η corresponding to a time-series signal is a shape parameter of generalized Gaussian distribution that approximates a histogram of a whitened spectral sequence, which is a sequence obtained by dividing a frequency domain sample sequence corresponding to the time-series signal by a spectral envelope estimated by regarding the η-th power of absolute values of the frequency domain sample sequence as a power spectrum; and the linear predictive coding apparatus comprises: a parameter determining part for determining a parameter η corresponding to the input time-series signal as η 1; a linear predictive analysis part for performing linear predictive analysis using a pseudo correlation function signal sequence obtained by performing inverse Fourier transform regarding the η 1 -th power of the absolute values of the frequency domain sample sequence corresponding to the time-series signal as a power spectrum to obtain LSP parameters; a code book storing part for storing a plurality of candidates optimized in order to code LSP parameters corresponding to a frequency domain sample for which the value of the parameter η is η 2; an adaptation part for adapting values of η for the plurality of candidates for LSP parameters stored in the code book storing part and the LSP parameters obtained by the linear predictive analysis part, the adaptation part being a linear transformation part adapted to perform linear transformation by the following expression, for at least one of each of the plurality of candidates for LSP parameters stored in the code book storing part and the LSP parameters obtained by the linear predictive analysis part, where p is an order of LSP parameters; the LSP parameters or the candidates for LSP parameters are indicated by ∧ ω[k][k=1,2,...,p]; the LSP parameters or the candidates for LSP parameters after the linear transformation are indicated by ∼ ω[k][k=1,2,...,p]; x 1,x 2,...x p, y 1,y 2,...y p-1, z 2,z 3,...z p are predetermined non-negative numbers; at least one of y 1,y 2,...y p-1, z 2,z 3,...z p is a predetermined positive number; and K is a matrix in which elements other than X 1,X 2,...X p, y 1,y 2,...y p-1, and z 2,z 3,...z p are 0, ω ̃ 1 ω ̃ 2 ⋮ ω ̃ p = K ω ^ 1 − π p + 1 ω ^ 2 − 2 ⁢ π p + 1 ⋮ ω ^ p − pπ p + 1 + ω ^ 1 ω ^ 2 ⋮ ω ^ p K = x 1 y 1 0 z 2 x 2 y 2 z 3 x 3 y 3 ⋱ ⋱ ⋱ ⋱ ⋱ 0 z p x p; and a coding part for obtaining a linear predictive coefficient code corresponding to the LSP parameters obtained by the linear predictive analysis part, using the plurality of candidates for LSP parameters and the LSP parameters for which the values of the η have been adapted. a parameter determining part for determining a parameter η corresponding to the input time-series signal as η 1; a linear predictive analysis part for performing linear predictive analysis using a pseudo correlation function signal sequence obtained by performing inverse Fourier transform regarding the η 1 -th power of the absolute values of the frequency domain sample sequence corresponding to the time-series signal as a power spectrum to obtain LSP parameters; a code book storing part for storing a plurality of candidates optimized in order to code LSP parameters corresponding to a frequency domain sample for which the value of the parameter η is η 2; an adaptation part for adapting values of η for the plurality of candidates for LSP parameters stored in the code book storing part and the LSP parameters obtained by the linear predictive analysis part, the adaptation part being a linear transformation part adapted to perform linear transformation by the following expression, for at least one of each of the plurality of candidates for LSP parameters stored in the code book storing part and the LSP parameters obtained by the linear predictive analysis part, where p is an order of LSP parameters; the LSP parameters or the candidates for LSP parameters are indicated by ∧ ω[k][k=1,2,...,p]; the LSP parameters or the candidates for LSP parameters after the linear transformation are indicated by ∼ ω[k][k=1,2,...,p]; x 1,x 2,...x p, y 1,y 2,...y p-1, z 2,z 3,...z p are predetermined non-negative numbers; at least one of y 1,y 2,...y p-1, z 2,z 3,...z p is a predetermined positive number; and K is a matrix in which elements other than X 1,X 2,...X p, y 1,y 2,...y p-1, and z 2,z 3,...z p are 0, ω ̃ 1 ω ̃ 2 ⋮ ω ̃ p = K ω ^ 1 − π p + 1 ω ^ 2 − 2 ⁢ π p + 1 ⋮ ω ^ p − pπ p + 1 + ω ^ 1 ω ^ 2 ⋮ ω ^ p K = x 1 y 1 0 z 2 x 2 y 2 z 3 x 3 y 3 ⋱ ⋱ ⋱ ⋱ ⋱ 0 z p x p; and a coding part for obtaining a linear predictive coefficient code corresponding to the LSP parameters obtained by the linear predictive analysis part, using the plurality of candidates for LSP parameters and the LSP parameters for which the values of the η have been adapted.