Re-examining selective adaptation: Fatiguing feature detectors, or distributional learning?

Abstract

When a listener hears many good examples of a /b/ in a row, they are less likely to classify other sounds on, e.g., a /b/-to-/d/ continuum as /b/. This phenomenon is known as selective adaptation and is a well-studied property of speech perception. Traditionally, selective adaptation is seen as a mechanistic property of the speech perception system, and attributed to fatigue in acoustic-phonetic feature detectors. However, recent developments in our understanding of non-linguistic sensory adaptation and higher-level adaptive plasticity in speech perception and language comprehension suggest that it is time to re-visit the phenomenon of selective adaptation. We argue that selective adaptation is better thought of as a computational property of the speech perception system. Drawing on a common thread in recent work on both non-linguistic sensory adaptation and plasticity in language comprehension, we furthermore propose that selective adaptation can be seen as a consequence of distributional learning across multiple levels of representation. This proposal opens up new questions for research on selective adaptation itself, and also suggests that selective adaptation can be an important bridge between work on adaptation in low-level sensory systems and the complicated plasticity of the adult language comprehension system.

The Role of Lexical Status and Individual Differences for Perceptual Learning in Younger and Older Adults

“…Thus it remains unclear whether distributional learning can reduce to selective adaptation and indeed, it has been argued that selective adaptation can be explained under the mechanisms of distributional learning (Kleinschmidt & Jaeger, 2015c) rather than the other way around. However, the difference in terminology should not interfere with our main interest of investigating the influence of topdown lexical knowledge in the perceptual learning of older adults.…”

Allophones, not phonemes in spoken-word recognition

“…But its popularity declined quickly due to findings that selective adaptation does not exclusively reveal feature detectors (Kleinschmidt & Jaeger, 2015;Remez, 1987). In this context, it is important to note that Samuel and Kat (1996) argued that selective adaptation arises at three levels: recognition of simple acoustic patterns (see also Holt, 2005Holt, , 2006, recognition of complex acoustic patterns, and recognition of phonetic categories.…”

Talker-specificity and adaptation in quantifier interpretation

“…Both of these quantities are of theoretical interest: talkers might differ in either or both of these aspects, so that the ability to adapt to such differences is potentially beneficial for listeners. Additionally, if lexical adaptation at least qualitatively follows the principles of rational inference and learning (as has been proposed for phonetic adaptation, Kleinschmidt & Jaeger, 2011, 2015, 2015b and syntactic adaptation, Fine, Qian, Jaeger, & Jacobs, 2010; Kleinschmidt, Fine, & Jaeger, 2012), listeners are expected to be sensitive to both prior probability of quantifiers (i.e., their frequency of use) and the likelihood of quantifiers given an intended interpretation (i.e., how quantifiers are used). Although not framed in these terms, previous work has exclusively focused on adaptation to changes in the frequency (and only for content words, e.g., Creel et al, 2008; Metzing & Brennan, 2003), leaving open whether listeners can adapt to changes in the likelihood.…”