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Abstract Humans implicitly pick up on probabilities of stimuli and events, yet it remains unclear how statistical learning builds expectations that affect perception. Across 29 experiments, we examine the influence of task-irrelevant distributions—defined across acoustic frequency—on both tone detection in noise and tone duration judgments. The shape and range of the frequency distributions impact suppression and enhancement effects, as does a given tone's position within the range. Perception adapts quickly to changing distributions, but past distributions influence future judgments. Massed exposure to a single frequency impacts perception along a range of subsequently encountered frequencies. A novel bias emerges as well: lower frequencies are perceived as longer and higher ones as shorter. Probability-driven learning dynamically shapes perception, driven by interacting influences of sensory processing, distributional learning, and selective attention that sculpt a gain function involving modest enhancement of more-likely stimuli, and robust suppression of less-likely stimuli. 

Speech conveys both linguistic messages and a wealth of social and identity information about a talker. This information arrives as complex variations across many acoustic dimensions. Ultimately, speech communication depends on experience within a language community to develop shared long-term knowledge of the mapping from acoustic patterns to the category distinctions that support word recognition, emotion evaluation, and talker identification. A great deal of research has focused on the learning involved in acquiring long-term knowledge to support speech categorization. Inadvertently, this focus may give the impression of a mature learning endpoint. Instead, there seems to be no firm line between perception and learning in speech. The contributions of acoustic dimensions are malleably reweighted continuously as a function of regularities evolving in short-term input. In this way, continuous learning across speech impacts the very nature of the mapping from sensory input to perceived category. This article presents a case study in understanding how incoming sensory input—and the learning that takes place across it—interacts with existing knowledge to drive predictions that tune the system to support future behavior. 

Abstract Perception changes rapidly and implicitly as a function of passive exposure to speech that samples different acoustic distributions. Past research has shown that this statistical learning generalizes across talkers and, to some extent, new items, but these studies involved listeners’ active engagement in processing statistics-bearing stimuli. In this study, we manipulated the relationship between voice onset time (VOT) and fundamental frequency (F0) to establish distributional regularities either aligned with American English or reversed to create a subtle foreign accent. We then tested whether statistical learning across passive exposure to these distributions generalized to new items never experienced in the accent. Experiment 1 showed statistical learning across passive exposure but no generalization of learning when exposure and test items shared the same initial consonant but differed in vowels (bear/pear → beer/pier) or when they differed in initial consonant but shared distributional regularities across VOT and F0 dimensions (deer/tear → beer/pier). Experiment 2 showed generalization to stimuli that shared the statistics-bearing phoneme (bear/pear → beer/pier), but only when the response set included tokens from both exposure and generalization stimuli. Moreover, statistical learning transferred to influence the subtle acoustics of listeners’ own speech productions but did not generalize to influence productions of stimuli not heard in the accent. In sum, passive exposure is thus sufficient to support statistical learning and its generalization, but task demands modulate this dynamic. Moreover, production does not simply mirror perception: generalization in perception was not accompanied by transfer to production. 

Abstract There is considerable lab‐based evidence for successful incidental learning, in which a learner's attention is directed away from the to‐be‐learned stimulus and towards another stimulus. In this study, we extend incidental learning research into the language learning classroom. Three groups of adult second language (L2) learners (N= 52) engaged in structured classroom Mandarin learning took part in an 8‐week study. One group served as a classroom‐only control group. The second group underwent additional intentional auditory training involving Mandarin speech and explicit feedback. The third group underwent additional incidental learning combined with nonspeech “perceptual building block” categories—categories that share critical perceptual dimensions with target L2 speech categories but that are not perceived as speech. We demonstrate that when supplemented with structured classroom learning, incidental learning involving nonspeech analogs promotes phonetic, category, and word learning equivalent to learning from more traditional intentional auditory training. 

Abstract Multilingual speakers can find speech recognition in everyday environments like restaurants and open-plan offices particularly challenging. In a world where speaking multiple languages is increasingly common, effective clinical and educational interventions will require a better understanding of how factors like multilingual contexts and listeners’ language proficiency interact with adverse listening environments. For example, word and phrase recognition is facilitated when competing voices speak different languages. Is this due to a “release from masking” from lower-level acoustic differences between languages and talkers, or higher-level cognitive and linguistic factors? To address this question, we created a “one-man bilingual cocktail party” selective attention task using English and Mandarin speech from one bilingual talker to reduce low-level acoustic cues. In Experiment 1, 58 listeners more accurately recognized English targets when distracting speech was Mandarin compared to English. Bilingual Mandarin–English listeners experienced significantly more interference and intrusions from the Mandarin distractor than did English listeners, exacerbated by challenging target-to-masker ratios. In Experiment 2, 29 Mandarin–English bilingual listeners exhibited linguistic release from masking in both languages. Bilinguals experienced greater release from masking when attending to English, confirming an influence of linguistic knowledge on the “cocktail party” paradigm that is separate from primarily energetic masking effects. Effects of higher-order language processing and expertise emerge only in the most demanding target-to-masker contexts. The “one-man bilingual cocktail party” establishes a useful tool for future investigations and characterization of communication challenges in the large and growing worldwide community of Mandarin–English bilinguals. 

Statistical learning (SL) is typically assumed to be a core mechanism by which organisms learn covarying structures and recurrent patterns in the environment, with the main purpose of facilitating processing of expected events. Within this theoretical framework, the environment is viewed as relatively stable, and SL ‘captures’ the regularities therein through implicit unsupervised learning by mere exposure. Focusing primarily on language— the domain in which SL theory has been most influential—we review evidence that the environment is far from fixed: it is dynamic, in continual flux, and learners are far from passive absorbers of regularities; they interact with their environments, thereby selecting and even altering the patterns they learn from. We therefore argue for an alternative cognitive architecture, where SL serves as a subcomponent of an information foraging (IF) system. IF aims to detect and assimilate novel recurrent patterns in the input that deviate from randomness, for which SL supplies a baseline. The broad implications of this viewpoint and their relevance to recent debates in cognitive neuroscience are discussed. 

The human auditory system consists of both peripheral and central components, both of which play a role but contribute distinctly to overall auditory functioning and can be differentially impacted by pathophysiologic states. Hemispheric surgery (HS), a procedure used for the treatment of drug-resistant epilepsy, involves com- plete disconnection of the auditory cortex in the operative hemisphere, leaving hearing acuity (peripheral function) intact but having heavy implications for auditory processing (central function). The literature describing pre- and post-operative auditory processing abilities of individuals who have undergone HS is sparse, but the research available provides evidence that several central auditory processes including auditory spatial analysis and temporal processing may be impacted. De昀椀cits noted in standardized testing within the clinical or research environment have concrete functional impacts that may be currently under-appreciated and could lead to under-utilization of appropriate therapeutic strategies and accommodations. This review describes the pro昀椀le of central auditory processing abilities in patients who have undergone HS by synthesizing available literature and incorporating research in other clinical populations to help 昀椀ll critical gaps in our understanding of how cerebral disconnection impacts the central auditory system. 

Abstract Communicating with a speaker with a different accent can affect one’s own speech. Despite the strength of evidence for perception-production transfer in speech, the nature of transfer has remained elusive, with variable results regarding the acoustic properties that transfer between speakers and the characteristics of the speakers who exhibit transfer. The current study investigates perception-production transfer through the lens of statistical learning across passive exposure to speech. Participants experienced a short sequence of acoustically variable minimal pair (beer/pier) utterances conveying either an accent or typical American English acoustics, categorized a perceptually ambiguous test stimulus, and then repeated the test stimulus aloud. In thecanonicalcondition, /b/–/p/ fundamental frequency (F0) and voice onset time (VOT) covaried according to typical English patterns. In thereversecondition, the F0xVOT relationship reversed to create an “accent” with speech input regularities atypical of American English. Replicating prior studies, F0 played less of a role in perceptual speech categorization in reverse compared with canonical statistical contexts. Critically, this down-weighting transferred to production, with systematic down-weighting of F0 in listeners’ own speech productions in reverse compared with canonical contexts that was robust across male and female participants. Thus, the mapping of acoustics to speech categories is rapidly adjusted by short-term statistical learning across passive listening and these adjustments transfer to influence listeners’ own speech productions.