TY - JOUR
T1 - Say when
T2 - An automated method for high-accuracy speech onset detection
AU - Jansen, Peter A.
AU - Waiter, Scott
N1 - Funding Information:
This project was supported by Natural Science and Engineering Research Council of Canada (NSERC) Grant 327454 to S.W. Our speech onset detection software is available from our Web site, cogsci.mcmaster.ca, or by contacting the authors.
PY - 2008/8
Y1 - 2008/8
N2 - 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 Say When-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.
AB - 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 Say When-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.
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U2 - 10.3758/BRM.40.3.744
DO - 10.3758/BRM.40.3.744
M3 - Article
C2 - 18697670
AN - SCOPUS:50849132515
SN - 1554-351X
VL - 40
SP - 744
EP - 751
JO - Behavior Research Methods
JF - Behavior Research Methods
IS - 3
ER -