A new formant tracking algorithm using phoneme depen-dent nominal formant values is tested. The algorithmcon-sists of three phases: (1) analysis, (2) segmentation, and (3) formant tracking. In the analysis phase, formant can-didates are obtained by solving for the roots of the lin-ear prediction polynomial. In the segmentation phase, the input text is converted into a sequence of phonemic symbols. Then the sequence is time aligned with the speech utterance. Finally, a set of formant candidates that are close to the nominal formant estimates while satisfy-ing the continuity constraints are chosen. The new algo-rithm significantly reduces the formant tracking error rate (3.62%) over a formant tracking algorithmusing only con-tinuity constraints (13.04%). We will also discuss how to further reduce the tracking error rate.