The Goldilocks Zone of Perceptual Learning

Bad maps may not always get you lost: Lexically driven perceptual recalibration for substituted phonemes

The speech perception system adjusts its phoneme categories based on the current speech input and lexical context. This is known as lexically driven perceptual recalibration, and it is often assumed to underlie accommodation to non-native accented speech. However, recalibration studies have focused on maximally ambiguous sounds (e.g., a sound ambiguous between "sh" and "s" in a word like "superpower"), a scenario that does not represent the full range of variation present in accented speech. Indeed, non-native speakers sometimes completely substitute a phoneme for another, rather than produce an ambiguous segment (e.g., saying "shuperpower"). This has been called a "bad map" in the literature. In this study, we scale up the lexically driven recalibration paradigm to such cases. Because previous research suggests that the position of the critically accented phoneme modulates the success of recalibration, we include such a manipulation in our study. And to ensure that participants treat all critical items as words (an important point for successful recalibration), we use a new exposure task that incentivizes them to do so. Our findings suggest that while recalibration is most robust after exposure to ambiguous sounds, it also occurs after exposure to bad maps. But interestingly, positional effects may be reversed: recalibration was more likely for ambiguous sounds late in words, but more likely for bad maps occurring early in words. Finally, a comparison of an online versus in-lab version of these conditions shows that experimental setting may have a non-trivial effect on the results of recalibration studies.

Hearing is believing: Lexically guided perceptual learning is graded to reflect the quantity of evidence in speech input

There is wide variability in the acoustic patterns that are produced for a given linguistic message, including variability that is conditioned on who is speaking. Listeners solve this lack of invariance problem, at least in part, by dynamically modifying the mapping to speech sounds in response to structured variation in the input. Here we test a primary tenet of the ideal adapter framework of speech adaptation, which posits that perceptual learning reflects the incremental updating of cue-sound mappings to incorporate observed evidence with prior beliefs. Our investigation draws on the influential lexically guided perceptual learning paradigm. During an exposure phase, listeners heard a talker who produced fricative energy ambiguous between /ʃ/ and /s/. Lexical context differentially biased interpretation of the ambiguity as either /s/ or /ʃ/, and, across two behavioral experiments (n = 500), we manipulated the quantity of evidence and the consistency of evidence that was provided during exposure. Following exposure, listeners categorized tokens from an ashi - asi continuum to assess learning. The ideal adapter framework was formalized through computational simulations, which predicted that learning would be graded to reflect the quantity, but not the consistency, of the exposure input. These predictions were upheld in human listeners; the magnitude of the learning effect monotonically increased given exposure to four, 10, or 20 critical productions, and there was no evidence that learning differed given consistent versus inconsistent exposure. These results (1) provide support for a primary tenet of the ideal adapter framework, (2) establish quantity of evidence as a key determinant of adaptation in human listeners, and (3) provide critical evidence that lexically guided perceptual learning is not a binary outcome. In doing so, the current work provides foundational knowledge to support theoretical advances that consider perceptual learning as a graded outcome that is tightly linked to input statistics in the speech stream.

Semantic context and stimulus variability independently affect rapid adaptation to non-native English speech in young adults

When speech is degraded or challenging to recognize, young adult listeners with normal hearing are able to quickly adapt, improving their recognition of the speech over a short period of time. This rapid adaptation is robust, but the factors influencing rate, magnitude, and generalization of improvement have not been fully described. Two factors of interest are lexico-semantic information and talker and accent variability; lexico-semantic information promotes perceptual learning for acoustically ambiguous speech, while talker and accent variability are beneficial for generalization of learning. In the present study, rate and magnitude of adaptation were measured for speech varying in level of semantic context, and in the type and number of talkers. Generalization of learning to an unfamiliar talker was also assessed. Results indicate that rate of rapid adaptation was slowed for semantically anomalous sentences, as compared to semantically intact or topic-grouped sentences; however, generalization was seen in the anomalous conditions. Magnitude of adaptation was greater for non-native as compared to native talker conditions, with no difference between single and multiple non-native talker conditions. These findings indicate that the previously documented benefit of lexical information in supporting rapid adaptation is not enhanced by the addition of supra-sentence context.

Perceptual tracking of distinct distributional regularities within a single voice

The speech signal is inherently variable and listeners need to recalibrate when local, short-term distributions of acoustic dimensions deviate from long-term representation. The present experiment investigated the specificity of this perceptual adjustment, addressing whether the perceptual system is capable of tracking differing simultaneous short-term acoustic distributions of the same speech categories, conditioned by context. The results indicated that instead of aggregating over the contextual variation, listeners tracked separate distributional statistics for instances of speech categories experienced in different phonetic/lexical contexts, suggesting that perceptual learning is not only influenced by distributional statistics, but also by external factors such as contextual information.