Auditory feedback has a crucial role in stably controlling speaking and singing. Formanttransformed auditory feedback (TAF) is used to investigate the relationship between perturbation to the formant frequency and the compensatory response to clarify the mechanism of auditory-speech motor control. Although previous studies for formant TAF applied linear predictive coding (LPC) to estimate formant frequencies, LPC estimates false formants for high-pitch voice. In this paper, we investigate how different vocal-tract spectrum estimation methods in real-time formant TAFs affect the compensatory response of formant frequencies to perturbations. A phase equalization-based autoregressive exogenous model (PEAR) is applied to the TAF system as a formant estimation method that can estimate the formant frequency more accurately and robustly than LPC can. Fifteen Japanese native speakers were asked to repeat the Japanese syllables /he/ or /hi/ while receiving feedback sounds whose formants F1 and F2 were transformed. From the results for the /he/ condition, the F1 compensatory response for PEAR was significantly larger than that of LPC, and the compensation error in the F1-F2 plane for PEAR was less than that for LPC. Our results suggest that PEAR can increase both the accuracy of formant frequency estimation and the naturalness of the transformed speech sound.