Abstract

For perceptual learning on fine-grained discrimination tasks, improvement can be enhanced or disrupted when two tasks are trained, depending on how the training on those tasks is distributed. To investigate if this phenomenon extends to speech learning, we trained native-English speakers to transcribe both Mandarin- and Turkish-accented English sentences using one of three different configurations of the same training stimuli. After training, all trained groups performed better than untrained controls, and similarly to each other, on a novel talker of a trained accent (Mandarin). However, for a novel accent (Slovakian), performance was better than untrained controls when training alternated between the two accents, but not when the two accents were trained consecutively. Performance for the novel accent decreased as the number of contiguous sentences per accent during training increased. One interpretation of these results is that accent information is integrated during a restricted time window. If two accents are encountered within this window, information from both accents is integrated, yielding accent-general learning. If two accents are encountered in separate consecutive windows, accent-specific learning occurs for each accent and accent-general learning is prevented. These results mirror patterns for fine-grained discrimination learning, and illuminate the processes underlying the success of high-variability training.

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