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Previously, it has been shown that using clear speech short-term spectra improves the intelligibility of conversational speech. In this paper, a speech transformation method is used to map the spectral features of conversational speech to resemble clear speech. A joint-density Gaussian mixture model is used as the mapping function. The transformation is studied in both the formant frequency and the line spectral frequency domains. Listening test results show that in noisier environments, the transformed speech signal improves vowel intelligibility signif- icantly compared to the original conversational speech. There is also an increase in vowel intelligibility in less noisy environ- ments, but the increase is not statistically significant. The significance tests are performed by Tukey comparison and planned one-tail t-test methods.