In sources used in oral history research (such as interviews with eye witnesses), passages where the degree of personal emotional involvement is found to be high can be of particular interest, as these may give insight into how historical events were experienced, and what moral dilemmas and psychological or religious struggles were encountered. The length of speech pauses are important paralinguistics cues reflecting the emotional state of a speaker (Tisljár-Szabo & Pléh, 2014) and these can be realised by silent pauses, filled pauses and word lengthening (Van Donzel & Koopmans-van Beinum, 1996).

In a pilot study involving a large corpus of interview recordings with Dutch war veterans, we have investigated if it is possible to develop a method for automatically identifying those passages where the degree of personal emotional involvement is high. The method is based on the automatic detection of exceptionally large silences and filled pause segments (using Automatic Speech Recognition), and cues taken from specific n-grams. The first results appear to be encouraging enough for further elaboration of the method.