title: SayWhen: an automated method for high-accuracy speech onset detection.
abstract: Many researchers across many experimental domains utilize the latency of spoken responses as a dependent measure. These measurements are typically made using a voice key, an electronic device that monitors the amplitude of a voice signal, and detects when a predetermined threshold is crossed. Unfortunately, voice keys have been repeatedly shown to be alarmingly errorful and biased in accurately detecting speech onset latencies. We present SayWhen--an easy-to-use software system for offline speech onset latency measurement that (1) automatically detects speech onset latencies with high accuracy, well beyond voice key performance, (2) automatically detects and flags a subset of trials most likely to have mismeasured onsets, for optional manual checking, and (3) implements a graphical user interface that greatly speeds and facilitates the checking and correction of this flagged subset of trials. This automatic-plus-selective-checking method approaches the gold standard performance of full manual coding in a small fraction of the time.
authors.affiliation: Department of Psychology, Neurosciences and Behaviour, McMaster University, Hamilton, Ontario, Canada. jansenpa@mcmaster.ca
authors.forename: Peter A
authors.initials: PA
authors.lastname: Jansen
authors.forename: Scott
authors.initials: S
authors.lastname: Watter
mesh_terms: D003201:Computers; D001330:Electronic Data Processing; D006801:Humans; D012815:Signal Processing, Computer-Assisted; D013060:Speech