Encoding lexical tones in jTRACE: a simulation of monosyllabic spoken word recognition in Mandarin Chinese.

Despite its prevalence as one of the most highly influential models of spoken word recognition, the TRACE model has yet to be extended to consider tonal languages such as Mandarin Chinese. A key reason for this is that the model in its current state does not encode lexical tone. In this report, we present a modified version of the jTRACE model in which we borrowed on its existing architecture to code for Mandarin phonemes and tones. Units are coded in a way that is meant to capture the similarity in timing of access to vowel and tone information that has been observed in previous studies of Mandarin spoken word recognition. We validated the model by first simulating a recent experiment that had used the visual world paradigm to investigate how native Mandarin speakers process monosyllabic Mandarin words (Malins & Joanisse, 2010). We then subsequently simulated two psycholinguistic phenomena: (1) differences in the timing of resolution of tonal contrast pairs, and (2) the interaction between syllable frequency and tonal probability. In all cases, the model gave rise to results comparable to those of published data with human subjects, suggesting that it is a viable working model of spoken word recognition in Mandarin. It is our hope that this tool will be of use to practitioners studying the psycholinguistics of Mandarin Chinese and will help inspire similar models for other tonal languages, such as Cantonese and Thai.