Abstract: For tracking multiple, simultaneous voices, predicted tracking is used to follow individual voices through time, even when the voices are very similar in fundamental frequency. An acoustic waveform comprised of a group of voices is submitted to a frequency estimator, which may employ an average magnitude difference function (AMDF) calculation to determine the voice fundamental frequencies that are present for each voice. These frequency estimates are then used as input values to a recurrent neural network that tracks each of the frequencies by predicting the current fundamental frequency value for each voice present based on past fundamental frequency values in order to disambiguate any fundamental frequency trajectories that may be converging in frequency.