A dereverberation apparatus for eliminating late reverberation from an acoustic signal having original acoustic signal and the late reverberation, the dereverberation apparatus comprising: a memory adapted to store multiple discrete acoustic signals for each of M channels, the multiple discrete acoustic signals of each channel m of the M channels representing sample values, obtained at multiple points in time, of the acoustic signal as observed by a respective one of M sensors, where m = 1 to M, M ≥ 1; a model application unit (10b, 310b, 500, 800) adapted to calculate, by using the discrete acoustic signals, linear prediction coefficients of a multi-step linear prediction model of channel w, where w = 1 to M; and a late reverberation predictor (10c, 310c) adapted to output predicted late reverberation of the channel w at a discrete time index n, characterized in that: the multi-step linear prediction model is x w n = ∑ m = 1 M ∑ p = 1 N / M α w, m p ⋅ x m ⁢ n - p - D + e w n where x w (n) is a discrete acoustic signal of the channel w at the discrete time index n, x m (n) is each of the discrete acoustic signals, x m (n) corresponds to each channel m at the discrete time index, n, α w,m,..., α w,m ([N/M]) are the linear prediction coefficients, e w (n) is the prediction error corresponding to the channel w at the discrete time index n, N is a positive integer, [●] is a Floor function, D is a constant representing a step size, and D ≥ 1; the late reverberation predictor is adapted to output a linear prediction value as the predicted late reverberation, the linear prediction value is obtained by substituting the linear prediction coefficients α w,m (p) and the discrete acoustic signals x m (n-P-D) into a linear prediction term ∑ m = 1 M ∑ p = 1 N / M α w, m p ⋅ x m ⁢ n - p - D of the multi-step linear prediction model. a memory adapted to store multiple discrete acoustic signals for each of M channels, the multiple discrete acoustic signals of each channel m of the M channels representing sample values, obtained at multiple points in time, of the acoustic signal as observed by a respective one of M sensors, where m = 1 to M, M ≥ 1; a model application unit (10b, 310b, 500, 800) adapted to calculate, by using the discrete acoustic signals, linear prediction coefficients of a multi-step linear prediction model of channel w, where w = 1 to M; and a late reverberation predictor (10c, 310c) adapted to output predicted late reverberation of the channel w at a discrete time index n, characterized in that: the multi-step linear prediction model is x w n = ∑ m = 1 M ∑ p = 1 N / M α w, m p ⋅ x m ⁢ n - p - D + e w n where x w (n) is a discrete acoustic signal of the channel w at the discrete time index n, x m (n) is each of the discrete acoustic signals, x m (n) corresponds to each channel m at the discrete time index, n, α w,m,..., α w,m ([N/M]) are the linear prediction coefficients, e w (n) is the prediction error corresponding to the channel w at the discrete time index n, N is a positive integer, [●] is a Floor function, D is a constant representing a step size, and D ≥ 1; the late reverberation predictor is adapted to output a linear prediction value as the predicted late reverberation, the linear prediction value is obtained by substituting the linear prediction coefficients α w,m (p) and the discrete acoustic signals x m (n-P-D) into a linear prediction term ∑ m = 1 M ∑ p = 1 N / M α w, m p ⋅ x m ⁢ n - p - D of the multi-step linear prediction model. the multi-step linear prediction model is x w n = ∑ m = 1 M ∑ p = 1 N / M α w, m p ⋅ x m ⁢ n - p - D + e w n where x w (n) is a discrete acoustic signal of the channel w at the discrete time index n, x m (n) is each of the discrete acoustic signals, x m (n) corresponds to each channel m at the discrete time index, n, α w,m,..., α w,m ([N/M]) are the linear prediction coefficients, e w (n) is the prediction error corresponding to the channel w at the discrete time index n, N is a positive integer, [●] is a Floor function, D is a constant representing a step size, and D ≥ 1; the late reverberation predictor is adapted to output a linear prediction value as the predicted late reverberation, the linear prediction value is obtained by substituting the linear prediction coefficients α w,m (p) and the discrete acoustic signals x m (n-P-D) into a linear prediction term ∑ m = 1 M ∑ p = 1 N / M α w, m p ⋅ x m ⁢ n - p - D of the multi-step linear prediction model.