A reliable method of determining the base frequency (F b ) for utterances of various speaking styles is critical to enabling stable command labeling in the Fujisaki model. To achieve stable command labeling for diverse expressions of speech, a linear fitted model was developed using the ten percentile F0 of each utterance from three corpora of various speaking styles (read, acted, and spontaneous) as the independent variable to estimate a consistent F b for each utterance. To assess the robustness of the model for unknown utterances, the model was applied to test data, including both open and corpus-open data not used for the model development, and the difference between the estimated F b and the trained labelers' annotated F b was calculated. As a result, the obtained estimation model was found to fit well to the manually labeled F b s by exhibiting a small root mean squared error (RMSE) of 0.096 and a high coefficient of determination (R 2 ) of 0.89 for the closed dataset. Moreover, the model also exhibited a small RMSE of 0.091 and a high R 2 of 0.92 for the corpus-open dataset. The results revealed that the proposed model can reliably estimate the F b of utterances with various speaking styles.