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A system is proposed for the automatic detection of high vocal effort in speech. The system is evaluated using both PCM-coded speech and AMRcoded telephone speech. In addition, the effect of far-end noise in the telephone conditions is studied using both matched-condition training and cases with additive noise mismatch. The proposed system is based on Bayesian classification of mel-frequency cepstral feature vectors. Concerning the MFCC feature extraction process, the substitution of a spectrum analysis method emphasizing the fine structure improves the results in the noisy cases.