Many modern speech bandwidth extension techniques predict the high-frequency band based on features extracted from the lower band. While this method works for certain types of speech, problems arise when the correlation between the low and the high bands is not sufficient for adequate prediction. These situations require that additional high-band information is sent to the decoder. This overhead information, however, can be cleverly quantized using human auditory system models. In this paper, we propose a novel speech compression method that relies on bandwidth extension. The novelty of the technique lies in an elaborate perceptual model that determines a quantization scheme for wideband recovery and synthesis. Furthermore, a source/filter bandwidth extension algorithm based on spectral spline fitting is proposed. Results reveal that the proposed system improves the quality of narrowband speech while performing at a lower bitrate. When compared to other wideband speech coding schemes, the proposed algorithms provide comparable speech quality at a lower bitrate.