Abstract
This study examines whether non-tone language listeners can acquire lexical tone categories distributionally and whether attention in the training phase modulates the effect of distributional learning. Native Australian English listeners were trained on a Thai lexical tone minimal pair and their performance was assessed using a discrimination task before and after training. During Training, participants either heard a Unimodal distribution that would induce a single central category, which should hinder their discrimination of that minimal pair, or a Bimodal distribution that would induce two separate categories that should facilitate their discrimination. The participants either heard the distribution passively (Experiments 1A and 1B) or performed a cover task during training designed to encourage auditory attention to the entire distribution (Experiment 2). In passive listening (Experiments 1A and 1B), results indicated no effect of distributional learning: the Bimodal group did not outperform the Unimodal group in discriminating the Thai tone minimal pairs. Moreover, both Unimodal and Bimodal groups improved above chance on most test aspects from Pretest to Posttest. However, when participants’ auditory attention was encouraged using the cover task (Experiment 2), distributional learning was found: the Bimodal group outperformed the Unimodal group on a novel test syllable minimal pair at Posttest relative to at Pretest. Furthermore, the Bimodal group showed above-chance improvement from Pretest to Posttest on three test aspects, while the Unimodal group only showed above-chance improvement on one test aspect. These results suggest that non-tone language listeners are able to learn lexical tones distributionally but only when auditory attention is encouraged in the acquisition phase. This implies that distributional learning of lexical tones is more readily induced when participants attend carefully during training, presumably because they are better able to compute the relevant statistics of the distribution.
Highlights
How do we learn the regularities that exist in our highly structured environment? One approach is that we learn by tracking the statistics—ranging from simple frequency counts to PLOS ONE | DOI:10.1371/journal.pone.0133446 July 27, 2015Distributional Learning of Lexical Tones: Attended vs. Unattended complex conditional probabilities—of the regularities in the environment
While the Bimodal group improved following training as predicted, so did the Unimodal group, which prevents us from conclusively claiming that there is an effect of distributional learning
When the results across both experiments are taken together, the negative effect of a unimodal distribution is evident when the training tokens are listened to attentively, but not when listened to passively. These studies were designed to add to the current distributional learning literature by examining whether: (i) non-tone language listeners are able to acquire lexical tone categories distributionally; and (ii) attention to the training task modulates the effect of distributional learning effect of lexical tones
Summary
How do we learn the regularities that exist in our highly structured environment? One approach is that we learn by tracking the statistics—ranging from simple frequency counts to PLOS ONE | DOI:10.1371/journal.pone.0133446 July 27, 2015Distributional Learning of Lexical Tones: Attended vs. Unattended complex conditional probabilities—of the regularities in the environment. Japanese listeners learn from their linguistic environment that there is only one category (unimodal or single peak distribution) along a particular acoustic dimension in Japanese, the Japanese /r/, whereas English listeners learn that there are two categories (bimodal distribution) along the same acoustic dimension, English /r/ and /l/, resulting in the well-known difficulty native Japanese adults face in discriminating English /r/ and /l/ [5] This form of phonetic category acquisition has been studied empirically with consonants [4,6,7,8] and vowels [9,10,11,12]. Distributional learning is said to occur when discrimination of the minimal pair (such as the end tokens of the continuum) by those trained on the bimodal distribution improve significantly more than those trained on the unimodal distribution
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