Age, Hearing, and the Perceptual Learning of Rapid Speech

Abstract

The effects of aging and age-related hearing loss on the ability to learn degraded speech are not well understood. This study was designed to compare the perceptual learning of time-compressed speech and its generalization to natural-fast speech across young adults with normal hearing, older adults with normal hearing, and older adults with age-related hearing loss. Early learning (following brief exposure to time-compressed speech) and later learning (following further training) were compared across groups. Age and age-related hearing loss were both associated with declines in early learning. Although the two groups of older adults improved during the training session, when compared to untrained control groups (matched for age and hearing), learning was weaker in older than in young adults. Especially, the transfer of learning to untrained time-compressed sentences was reduced in both groups of older adults. Transfer of learning to natural-fast speech occurred regardless of age and hearing, but it was limited to sentences encountered during training. Findings are discussed within the framework of dynamic models of speech perception and learning. Based on this framework, we tentatively suggest that age-related declines in learning may stem from age differences in the use of high- and low-level speech cues. These age differences result in weaker early learning in older adults, which may further contribute to the difficulty to perceive speech in daily conversational settings in this population.

Rapid Perceptual Learning: A Potential Source of Individual Differences in Speech Perception Under Adverse Conditions?

“…Although highly compressed speech is initially hard to recognize, recognition accuracy improves quite rapidly with exposure to as few as 10 to 20 time-compressed sentences (e.g., Dupoux & Green, 1997;Golomb et al, 2007). This rapid learning has been shown in young and in older adults as well as in older adults with hearing impairments (Golomb et al, 2007;Manheim et al, 2018;Peelle & Wingfield, 2005). Finally, across age and hearing levels, we previously reported that variance in rapid learning of TCS accounted for unique variance in the recognition of NFS, even after controlling for the known association between the recognition of NFS and TCS (Manheim et al, 2018).…”

“…As for learning, perceptual learning for speech is certainly present in older adults with either normal or impaired hearing (Colby et al, 2018;Golomb et al, 2007;Karawani et al, 2016;Manheim et al, 2018;Neger et al, 2014;Peelle & Wingfield, 2005;Schlueter et al, 2016). However, whereas some reported little or no effects of age on learning (Golomb et al, 2007;Peelle & Wingfield, 2005), others found that learning might slow (Manheim et al, 2018) or diminish (Neger et al, 2014) with age. One possibility is that learning is maintained to a greater extent in situations in which lexical information can be used (Colby et al, 2018;Scharenborg & Janse, 2013).…”

“…Although ideally baseline recognition of TCS should have been estimated prior to the estimation of learning, here this assessment in young adults was conducted as part of the hearing assessment that was conducted either before or after the learning assessment. We nevertheless believe that this choice had minimal influence on the findings because even with substantially longer learning experience improvement in the recognition of new sentences produced by a different talker is minimal (e.g., Manheim et al, 2018).…”

Rapid Perceptual Learning and Individual Differences in Speech Perception: The Good, the Bad, and the Sad

“…In a series of studies, we found that individual differences in rapid perceptual learning of one type of distorted speech (e.g., time-compressed speech) were consistently related to individual differences in speech perception under different adverse conditions (e.g., speech in noise) Karawani et al, 2017;Manheim et al, 2018;Rotman et al, 2020). Furthermore, these associations could not be explained by correlations in performance across adverse conditions.…”

“…are met (Manheim, Lavie, & Banai, 2018;Rotman, Lavie, & Banai, 2020). Consistent with this hypothesis, a recent study of visual tasks and auditory frequency discrimination suggests that a common perceptual learning factor accounts for approximately 30% of the variance across different learning conditions (Yang et al, 2020), but whether the same holds true for rapid learning of speech is at present unclear.…”