In this paper we propose to apply formant pattern recognition to Mandarin vowel pronunciation assessment. We devise a novel pitch cycle detection method and suggest estimating formant frequencies from observations of the frequency domain by using pitch-synchronous analysis. Statistically based classifiers are trained to discriminate formant patterns for vowel pronunciation assessment. Five confusable Mandarin vowels are selected for experiments. Assessment results show an average human-machine score correlation improvement of 6.10% of the new method over ASR technique, and show an average improvement of 6.37% over traditional LPC analyzing method.