Effects of stimulus repetition and training schedule on the perceptual learning of time-compressed speech and its transfer

Attention, Perception, & Psychophysics(2019)

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摘要
Perceptual learning can facilitate the recognition of hard-to-perceive (e.g., time-compressed or spectrally-degraded) speech. Although the learning induced by training with time-compressed speech is robust, previous findings suggest that intensive training yields learning that is partially specific to the items encountered during practice. Here, we asked whether three parameters of the training procedure – the overall number of training trials (training intensity), how these trials are distributed across sessions, and the number of semantically different items encountered during training (set size) – influence learning and transfer. Different groups of participants (69 normal-hearing young adults; nine to 11 participants/group) completed different training protocols (or served as an untrained control group) and tested on the recognition of time-compressed sentences taken from the training set (learning), new time-compressed sentences presented by the trained talker (semantic transfer), and time-compressed sentences taken from the training set but presented by a different talker (acoustic transfer). Compared to untrained listeners, all training protocols yielded both learning and transfer. More intense training resulted in greater item-specific learning and greater acoustic transfer than less intense training with the same number of training sessions. Training on a smaller set size (i.e., greater token repetition during training) also resulted in greater acoustic transfer, whereas distributing practice over a number of sessions improved semantic transfer. Together, these data suggest that whereas practice on a small set that results in stimulus repetition during training is not harmful for learning, distributed training can support transfer to new stimuli, perhaps because it provides multiple opportunities to consolidate learning.
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关键词
Degraded speech,Rapid speech,Auditory learning,Generalization,Time-compressed speech
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