Estimating vowel formant discrimination thresholds using a single-interval classification task.

Previous research estimating vowel formant discrimination thresholds in words and sentences has often employed a modified two-alternative-forced-choice (2AFC) task with adaptive tracking. Although this approach has produced stable data, the length and number of experimental sessions, as well as the unnaturalness of the task, limit generalizations of results to ordinary speech communication. In this exploratory study, a typical identification task was used to estimate vowel formant discrimination thresholds. Specifically, a signal detection theory approach was used to develop a method to estimate vowel formant discrimination thresholds from a quicker, more natural single-interval classification task. In experiment 1 "classification thresholds" for words in isolation and embedded in sentences were compared to previously collected 2AFC data. Experiment 2 used a within-subjects design to compare thresholds estimated from both classification and 2AFC tasks. Due to instabilities observed in the experiment 1 sentence data, experiment 2 examined only isolated words. Results from these experiments show that for isolated words, thresholds estimated using the classification procedure are comparable to those estimated using the 2AFC task. These results, as well as an analysis of several aspects of the classification procedure, support the viability of this new approach for estimating discrimination thresholds for speech stimuli.