Sleep-Based Memory Consolidation Stabilizes Perceptual Learning of Noise-Vocoded Speech

Sleep-based memory consolidation has been shown to facilitate perceptual learning of atypical speech input including nonnative speech sounds, accented speech, and synthetic speech. The current research examined the role of sleep-based memory consolidation on perceptual learning for noise-vocoded speech, including maintenance of learning over a 1-week time interval. Because comprehending noise-vocoded speech requires extensive restructuring of the mapping between the acoustic signal and prelexical representations, sleep consolidation may be critical for this type of adaptation. Thus, the purpose of this study was to investigate the role of sleep-based memory consolidation on adaptation to noise-vocoded speech in listeners without hearing loss as a foundational step toward identifying parameters that can be useful to consider for auditory training with clinical populations.

Two groups of normal-hearing listeners completed a transcription training task with feedback for noise-vocoded sentences in either the morning or the evening. Learning was assessed through transcription accuracy before training, immediately after training, 12 hr after training, and 1 week after training for both trained and novel sentences.

Both the morning and evening groups showed improved comprehension of noise-vocoded sentences immediately following training. Twelve hours later, the evening group showed stable gains (following a period of sleep), whereas the morning group demonstrated a decline in gains (following a period of wakefulness). One week after training, the morning and evening groups showed equivalent performance for both trained and novel sentences.

Sleep-consolidated learning helps stabilize training gains for degraded speech input, which may hold clinical utility for optimizing rehabilitation recommendations.