While attempts to assess the level of stress present in an individual by analyzing his speech have shown some success, current methodology is best described as being capable of determining whether a talker is presently experiencing either minimum or maximum stress. For example, Jones (1990) found that, for those extremes of stress, both the increase in speaking fundamental frequency and the decrease in vocal jitter were statistically significant. Neither measure, however, was capable of distinguishing any intervening levels. Researchers continue searching for acoustic measures that might more precisely indicate ongoing changes in stress to establish a metric capable of more than simply differentiating between the two extremes. The objective is to distinguish among several levels of stress or to furnish a continuous, concurrent estimate of the talker's state. Two main components are considered for improving the estimation of a talker's actual stress level: 1) refinements in the acquisition of signals and their processing; and 2) proposals concerning the choice of acoustic parameters. The first objective is intended to maintain signal fidelity which should enhance the potential to detect changes in the speaker's voice. For acquisition of the acoustic signal, direct sampling and storing to a computer is highly recommended, thus eliminating the potential distortion that is inherent in tape recording. During the analog-to-digital conversion phase, the highest sample rates attainable in the face of storage limitations and the finer amplitude resolution provided by 16 bit converters should also be beneficial. Concerning the selection of acoustic parameters, in addition to speaking fundamental frequency and jitter, certain variations in the waveform (spectrum) might be exploited. The maximum rate of change in amplitude during a pitch period or the ratio of the energy in various segments of the spectrum, after each has been appropriately normalized, might not only indicate stress levels but also be independent of speaker variability.
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