Abstract
Recognizing acoustically degraded speech relies on predictive processing whereby incomplete auditory cues are mapped to stored linguistic representations via pattern recognition processes. While listeners vary in their ability to recognize degraded speech, performance improves when a written transcription is presented, allowing completion of the partial sensory pattern to preexisting representations. Building on work characterizing predictive processing as pattern completion, we examined the relationship between domain-general pattern recognition and individual variation in degraded speech learning. Participants completed a visual pattern recognition task to measure individual-level tendency towards pattern completion. Participants were also trained to recognize noise-vocoded speech with written transcriptions and tested on speech recognition pre- and post-training using a retrieval-based transcription task. Listeners significantly improved in recognizing speech after training, and pattern completion on the visual task predicted improvement for novel items. The results implicate pattern completion as a domain-general learning mechanism that can facilitate speech adaptation in challenging contexts.
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