The objective of this study was to develop a method to use digital signal processing (DSP) technology to describe quantitatively and statistically swallow-associated sounds in preterm infants and to use this method to analyze changes as infants mature. Twelve recordings of accelerometric and physiological data on bottle-feeding preterm infants between 32 and 39 weeks' postmenstrual age (PMA) were analyzed. Cervical auscultation was performed using an accelerometer attached over the larynx. Acoustic data were recorded and graphically displayed using DSP software. Initial discrete sounds (IDSs) were identified and used to construct an average waveform from which a ‘variance index’ (VI) was calculated for each infant. The shape of the IDS waveforms became progressively more uniform with advancing PMA, as indicated by a significant inverse correlation between VI and PMA (r=0.739; p=0.006). DSP technology facilitated the development of a new method to quantitatively analyze feeding in preterm infants. This method provides an elegant tool to track maturation of infant feeding and assessing feeding readiness. This technique makes the interpretation of cervical auscultation data less subjective by replacing the verbal description of the sounds of feeding with quantitative numeric values. It is anticipated that this method can be automated to facilitate further the analysis of cervical accelerometry data.