Previous work on automatic VOT measurement has focused on positive-valued VOT. However, in many languages VOT can be either positive or negative (prevoiced). We present a discriminative algorithm that simultaneously decides whether a stop is prevoiced and measures its VOT. The algorithm operates on feature functions designed to locate the burst and voicing onsets in the positive and negative VOT cases. Tested on a database of positive- and negative-VOT voiced stops, the algorithm predicts prevoicing with >90% accuracy, and gives good agreement between automatic and manual measurements.
Index Terms: voice onset time, automatic phonetic measurement, discriminative methods, structured prediction
Bibliographic reference. Henry, Katharine / Sonderegger, Morgan / Keshet, Joseph (2012): "Automatic measurement of positive and negative voice onset time", In INTERSPEECH-2012, 871-874.