A method for determining an enhanced mean opinion score, eMOS, predictive model for an adaptive streaming apparatus which is configured to encode a sample video into videos at different bit rates, the method comprising: pre-processing a peak signal to noise ratio, PSNR, of each segment of an encoded sample video at each bit rate to obtain a differential peak signal to noise ratio, dPSNR, wherein the dPSNR of each segment at each bit rate is a difference between a PSNR of the segment at the bit rate and a PSNR of the corresponding segment in the same sample video encoded at a maximum bit rate; determining, for multiple sample videos each a preset parameter that is of a received version of the sample video according to the dPSNR of each segment at each bit rate, wherein the preset parameter comprises a mean differential peak signal to noise ratio, mean (dPSNR), a maximum differential peak signal to noise ratio, max (dPSNR), a minimum differential peak signal to noise ratio, min (dPSNR), and a variance differential peak signal to noise ratio, std (dPSNR); determining an enhanced peak signal to noise ratio, ePSNR, predictive model by performing linear fitting on the preset parameters of all the sample videos and the corresponding mean opinion scores, MOSs, wherein ePSNR = a × mean (dPSNR) + b × max (dPSNR) + c × min (dPSNR) + d × std (dPSNR), and a, b, c, and d are a group of parameters that enable correlation between the ePSNR and the MOS to be the largest; and determining an enhanced mean opinion score, eMOS, predictive model by performing linear fitting on the ePSNR determined according to the ePSNR predictive model, and a corresponding mean opinion score, MOS, wherein eMOS = e × ePSNR + f. pre-processing a peak signal to noise ratio, PSNR, of each segment of an encoded sample video at each bit rate to obtain a differential peak signal to noise ratio, dPSNR, wherein the dPSNR of each segment at each bit rate is a difference between a PSNR of the segment at the bit rate and a PSNR of the corresponding segment in the same sample video encoded at a maximum bit rate; determining, for multiple sample videos each a preset parameter that is of a received version of the sample video according to the dPSNR of each segment at each bit rate, wherein the preset parameter comprises a mean differential peak signal to noise ratio, mean (dPSNR), a maximum differential peak signal to noise ratio, max (dPSNR), a minimum differential peak signal to noise ratio, min (dPSNR), and a variance differential peak signal to noise ratio, std (dPSNR); determining an enhanced peak signal to noise ratio, ePSNR, predictive model by performing linear fitting on the preset parameters of all the sample videos and the corresponding mean opinion scores, MOSs, wherein ePSNR = a × mean (dPSNR) + b × max (dPSNR) + c × min (dPSNR) + d × std (dPSNR), and a, b, c, and d are a group of parameters that enable correlation between the ePSNR and the MOS to be the largest; and determining an enhanced mean opinion score, eMOS, predictive model by performing linear fitting on the ePSNR determined according to the ePSNR predictive model, and a corresponding mean opinion score, MOS, wherein eMOS = e × ePSNR + f.