From a very brief speech, human listeners can estimate the pitch range of the speaker and normalize pitch perception. Spectral features which inherently involve both articulatory and phonatory characteristics were speculated to play roles in this process, but few were reported to directly correlate with speaker’s F0 range. To mimic this human auditory capability and validate the speculation, in a preliminary study we proposed an LSTM-based method to estimate speaker’s F0 range from a 300 ms-long speech input, which turned out to outperform the conventional method. By two more experiments, this study further improved the method and verified its validity in estimating the speaker-specific underlying F0 range. After incorporating a novel measurement of F0 range and a multi-task training approach, Experiment 1 showed that the refined model gave more accurate estimates than the initial model. Based on a Japanese-Chinese bilingual parallel speech corpus, Experiment 2 found that the F0 ranges estimated with the model from the Chinese speech and the model from the Japanese speech produced by the same set of speakers had no significant difference, whereas the conventional method showed significant difference. The results indicate that the proposed spectrum-based method captures the speaker-specific underlying F0 range which is independent of the linguistic content.