Respiratory sound analysis is a simple and noninvasive way to study the pathophysiology of the upper airway (UA). Recently, it has been used to diagnose partial or complete UA collapse in patients with obstructive sleep apnea (OSA). In this study, we investigated whether fluid accumulation in the neck alters the properties of respiratory sounds in temporal and spectral domains and whether the respiratory sounds analysis can be used to monitor variations in the physiology of the UA, as rejected by UA resistance (R(UA)). We recorded respiratory sounds and R(UA) from 19 individuals while awake. We applied lower body positive pressure (LBPP) to shift fluid out of the legs and into the neck, which increased R(UA). We calculated first and second formants and energy of inspiratory sound segments. Our results show that during both control (no LBPP) and LBPP arms of the study, the extracted features were different for the sound segments corresponding to low and high R(UA). Also, the features were different during control and LBPP arms of the study. With the application of support vector machine (SVM) based classifier, we were able to classify the sound segments into two groups of high/low resistance during control and LBPP arms and into two groups of control/LBPP when including all sound segments. The accuracies of non-linear SVM classifier were 74.5 ± 19.5%, 75.0 ± 15.4% and 77.1 ± 12.3% for the control arm, LBPP arm and between the arms, respectively. We also showed that during the LBPP arm, the variations in first formant of the sound segments corresponding to low and high R(UA) was much less than during the control arm. This indicates that with application of LBPP and accumulation of fluid in the neck, there are less variations in the morphology of the UA in response to changes in R(UA), than during the control arm. These results indicate that acoustic analysis of respiratory sounds can be used to investigate physiology of the UA and how interventions can alter UA properties.