It is well known that the human voice contains important information about the affective state of a speaker at a nonverbal level. Accordingly, we started an extensive investigation which aims at modelling intraindividual changes of the global affective state over time, as this state is reflected by the human voice, and can be inferred from measurable speech parameters. For the purpose of this investigation, a speech-recording procedure was designed which is especially suited to reveal intraindividual changes of voice patterns over time since each person serves as his or her own reference. On the other hand, the chosen experimental setup is less suited to classify patients in the sense of a traditional diagnostic scheme. In order to find an appropriate mathematical model on the basis of speech parameters, a calibration study with 190 healthy subjects was carried out which enabled us to investigate each parameter for its reproducibility, sensitivity and specificity. In particular, this calibration study yielded the information of how to draw the line between ‘normal’ fluctuations and ‘significant’ intraindividual changes over time. All speech parameters under discussion turned out to be sufficiently stable over time, whereas, in regard to their sensitivity to form and content of text, significant differences showed up. In a second step, a pilot study with 6 depressive patients was carried out in order to investigate the specificity of voice parameters with regard to psychopathology. It turned out that the registration procedure is realizable even if patients are considerably handicapped by their illness. However, no consistent correlations could be revealed between single speech parameters and psychopathological rating scales. Consequently, no simple mathematical model seems to apply in general, and, hence, we are working on a more sophisticated, multivariate method of a