- Detecting categorical perception in continuous discrimination data
- Speech Communication
- Volume | Issue number
- 55 | 1
- Number of pages
- Document type
- Faculty of Humanities (FGw)
- Amsterdam Center for Language and Communication (ACLC)
We present a method for assessing categorical perception from continuous discrimination data. Until recently, categorical perception of speech has exclusively been measured by discrimination and identification experiments with a small number of different stimuli, each of which is presented multiple times. Experiments by Rogers and Davis (2009), however, suggest that using non-repeating stimuli yields a more reliable measure of categorization. If this idea is applied to a single phonetic continuum, the continuum has to be densely sampled and the obtained discrimination data is nearly continuous. In the present study, we describe a maximum-likelihood method that is appropriate for analysing such continuous discrimination data.
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