Previous work has defined acoustic absement as the sum of acoustic distance between two time-series, such as words, over time. This process produces the time–distance product form of absement, an integral relation to distance. The related time–displacement product has not yet been formulated for acoustic data in the context of speech communication. Displacement, as a vector instead of a scalar, has the potential to better characterize acoustic differences since the dimensions in which two sounds vary are not compressed into a single number. In the present study, I present a method for calculating the time–displacement product for acoustic absement. The method relies on using a dynamic time warping framework, but instead of minimizing the accumulated distance at each time point, it minimizes the magnitude of the accumulated displacement vector between two time series. The magnitude of the final displacement vector is validated as a predictor of response latency in auditory lexical decision, where it shows a much lower correlation with item duration than the time–distance product of acoustic absement. The results of the validation serve to explore how the accumulation of distance between lexical candidates during spoken word recognition influences listener behavior.
Matthew C. Kelley (Wed,) studied this question.