Perceptual learning and speech processing: The good, the bad and the puzzling

Different forms of auditory training have a long history in the fields of audiology and speech and language therapy (SLT).

Sadly, these interventions which are based on perceptual learning have limited efficacy (see Lawrence et al., 2018 and Reyes et al., 2019 for recent meta-analyses), raising questions about the function of perceptual learning in humans beyond infancy. We suggest that rather than past perceptual learning serving future needs, rapid ongoing learning serves to support perception ‘online’.

The goal of this talk is to present an overview of the work conducted in my lab to explore this hypothesis and its implications for SLT and audiology. We use speech perception in adverse conditions as a model and study both typical and atypical  (e.g., non-native or hearing impaired) listeners.

Our studies are consistent with three broad conclusions. First, rapid perceptual learning on one speech task is predictive of individual differences in speech perception under independent adverse conditions. This remains true even after the contribution of cognitive and sensory factors that are known to associate with both perception and learning are considered.

Second, rapid perceptual learning is reduced in situations that are known to challenge speech perception, for example in non-native listening environments and in elderly listeners. Again, this is true regardless of other sensory and cognitive factors.

Third, rapid perceptual learning and learning that follows auditory training follow similar patterns of leaning specificity, thus the disappointing outcomes of auditory training protocols in the clinic might be a feature rather than an unfortunate bug.

Although our studies are correlational in nature, the idea that rapid learning is one of the factors involved in ongoing speech perception under adverse conditions is a parsimonious account consistent not only with our data but with other findings on speech perception and auditory training.