Examining the Relationship Between Multiple Tests of Receptive Vocabulary.

PURPOSE: Numerous tasks have been developed to measure receptive vocabulary, many of which were designed to be administered in person with a trained researcher or clinician. The purpose of the current study is to compare a common, in-person test of vocabulary with other vocabulary assessments that can be self-administered. METHOD: Fifty-three participants completed the Peabody Picture Vocabulary Test (PPVT) via online video call to mimic in-person administration, as well as four additional fully automated, self-administered measures of receptive vocabulary. Participants also completed three control tasks that do not measure receptive vocabulary. RESULTS: Pearson correlations indicated moderate correlations among most of the receptive vocabulary measures (approximately r = .50-.70). As expected, the control tasks revealed only weak correlations to the vocabulary measures. However, subsets of items of the four self-administered measures of receptive vocabulary achieved high correlations with the PPVT (r > .80). These subsets were found through a repeated resampling approach. CONCLUSIONS: Measures of receptive vocabulary differ in which items are included and in the assessment task (e.g., lexical decision, picture matching, synonym matching). The results of the current study suggest that several self-administered tasks are able to achieve high correlations with the PPVT when a subset of items are scored, rather than the full set of items. These data provide evidence that subsets of items on one behavioral assessment can more highly correlate to another measure. In practical terms, these data demonstrate that self-administered, automated measures of receptive vocabulary can be used as reasonable substitutes of at least one test (PPVT) that requires human interaction. That several of the fully automated measures resulted in high correlations with the PPVT suggests that different tasks could be selected depending on the needs of the researcher. It is important to note the aim was not to establish clinical relevance of these measures, but establish whether researchers could use an experimental task of receptive vocabulary that probes a similar construct to what is captured by the PPVT, and use these measures of individual differences.

Talker adaptation or "talker" adaptation? Musical instrument variability impedes pitch perception.

Listeners show perceptual benefits (faster and/or more accurate responses) when perceiving speech spoken by a single talker versus multiple talkers, known as talker adaptation. While near-exclusively studied in speech and with talkers, some aspects of talker adaptation might reflect domain-general processes. Music, like speech, is a sound class replete with acoustic variation, such as a multitude of pitch and instrument possibilities. Thus, it was hypothesized that perceptual benefits from structure in the acoustic signal (i.e., hearing the same sound source on every trial) are not specific to speech but rather a general auditory response. Forty nonmusician participants completed a simple musical task that mirrored talker adaptation paradigms. Low- or high-pitched notes were presented in single- and mixed-instrument blocks. Reflecting both music research on pitch and timbre interdependence and mirroring traditional "talker" adaptation paradigms, listeners were faster to make their pitch judgments when presented with a single instrument timbre relative to when the timbre was selected from one of four instruments from trial to trial. A second experiment ruled out the possibility that participants were responding faster to the specific instrument chosen as the single-instrument timbre. Consistent with general theoretical approaches to perception, perceptual benefits from signal structure are not limited to speech.

Using TMS to evaluate a causal role for right posterior temporal cortex in talker-specific phonetic processing.

Theories suggest that speech perception is informed by listeners' beliefs of what phonetic variation is typical of a talker. A previous fMRI study found right middle temporal gyrus (RMTG) sensitivity to whether a phonetic variant was typical of a talker, consistent with literature suggesting that the right hemisphere may play a key role in conditioning phonetic identity on talker information. The current work used transcranial magnetic stimulation (TMS) to test whether the RMTG plays a causal role in processing talker-specific phonetic variation. Listeners were exposed to talkers who differed in how they produced voiceless stop consonants while TMS was applied to RMTG, left MTG, or scalp vertex. Listeners subsequently showed near-ceiling performance in indicating which of two variants was typical of a trained talker, regardless of previous stimulation site. Thus, even though the RMTG is recruited for talker-specific phonetic processing, modulation of its function may have only modest consequences.

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.

Sleep-Based Memory Consolidation Stabilizes Perceptual Learning of Noise-Vocoded Speech.

PURPOSE: Sleep-based memory consolidation has been shown to facilitate perceptual learning of atypical speech input including nonnative speech sounds, accented speech, and synthetic speech. The current research examined the role of sleep-based memory consolidation on perceptual learning for noise-vocoded speech, including maintenance of learning over a 1-week time interval. Because comprehending noise-vocoded speech requires extensive restructuring of the mapping between the acoustic signal and prelexical representations, sleep consolidation may be critical for this type of adaptation. Thus, the purpose of this study was to investigate the role of sleep-based memory consolidation on adaptation to noise-vocoded speech in listeners without hearing loss as a foundational step toward identifying parameters that can be useful to consider for auditory training with clinical populations. METHOD: Two groups of normal-hearing listeners completed a transcription training task with feedback for noise-vocoded sentences in either the morning or the evening. Learning was assessed through transcription accuracy before training, immediately after training, 12 hr after training, and 1 week after training for both trained and novel sentences. RESULTS: Both the morning and evening groups showed improved comprehension of noise-vocoded sentences immediately following training. Twelve hours later, the evening group showed stable gains (following a period of sleep), whereas the morning group demonstrated a decline in gains (following a period of wakefulness). One week after training, the morning and evening groups showed equivalent performance for both trained and novel sentences. CONCLUSION: Sleep-consolidated learning helps stabilize training gains for degraded speech input, which may hold clinical utility for optimizing rehabilitation recommendations.

Phonetic categorization relies on motor simulation, but combinatorial phonological computations are abstract.

To identify a spoken word (e.g., dog), people must categorize the speech steam onto distinct units (e.g., contrast dog/fog,) and extract their combinatorial structure (e.g., distinguish dog/god). However, the mechanisms that support these two core functions are not fully understood. Here, we explore this question using transcranial magnetic stimulation (TMS). We show that speech categorization engages the motor system, as stimulating the lip motor area has opposite effects on labial (ba/pa)- and coronal (da/ta) sounds. In contrast, the combinatorial computation of syllable structure engages Broca's area, as its stimulation disrupts sensitivity to syllable structure (compared to motor stimulation). We conclude that the two ingredients of language-categorization and combination-are distinct functions in human brains.

Do individual differences in lexical reliance reflect states or traits?

Research suggests that individuals differ in the degree to which they rely on lexical information to support speech perception. However, the locus of these differences is not yet known; nor is it known whether these individual differences reflect a context-dependent "state" or a stable listener "trait." Here we test the hypothesis that individual differences in lexical reliance are a stable trait that is linked to individuals' relative weighting of lexical and acoustic-phonetic information for speech perception. At each of two sessions, listeners (n = 73) completed a Ganong task, a phonemic restoration task, and a locally time-reversed speech task - three tasks that have been used to demonstrate a lexical influence on speech perception. Robust lexical effects on speech perception were observed for each task in the aggregate. Individual differences in lexical reliance were stable across sessions; however, relationships among the three tasks in each session were weak. For the Ganong and locally time-reversed speech tasks, increased reliance on lexical information was associated with weaker reliance on acoustic-phonetic information. Collectively, these results (1) provide some evidence to suggest that individual differences in lexical reliance for a given task are a stable reflection of the relative weighting of acoustic-phonetic and lexical cues for speech perception in that task, and (2) highlight the need for a better understanding of the psychometric characteristics of tasks used in the psycholinguistic domain to build theories that can accommodate individual differences in mapping speech to meaning.

Validation of two measures for assessing English vocabulary knowledge on web-based testing platforms: long-form assessments.

The goal of the current work was to develop and validate web-based measures for assessing English vocabulary knowledge. Two existing paper-and-pencil assessments, the Vocabulary Size Test (VST) and the Word Familiarity Test (WordFAM), were modified for web-based administration. In Experiment 1, participants (n = 100) completed the web-based VST. In Experiment 2, participants (n = 100) completed the web-based WordFAM. Results from these experiments confirmed that both tasks (1) could be completed online, (2) showed expected sensitivity to English frequency patterns, (3) exhibited high internal consistency, and (4) showed an expected range of item discrimination scores, with low frequency items exhibiting higher item discrimination scores compared to high frequency items. This work provides open-source English vocabulary knowledge assessments with normative data that researchers can use to foster high quality data collection in web-based environments.

Validation of two measures for assessing English vocabulary knowledge on web-based testing platforms: brief assessments.

Two measures for assessing English vocabulary knowledge, the Vocabulary Size Test (VST) and the Word Familiarity Test (WordFAM), were recently validated for web-based administration. An analysis of the psychometric properties of these assessments revealed high internal consistency, suggesting that stable assessment could be achieved with fewer test items. Because researchers may use these assessments in conjunction with other experimental tasks, the utility may be enhanced if they are shorter in duration. To this end, two "brief" versions of the VST and the WordFAM were developed and submitted to validation testing. Each version consisted of approximately half of the items from the full assessment, with novel items across each brief version. Participants (n = 85) completed one brief version of both the VST and the WordFAM at session one, followed by the other brief version of each assessment at session two. The results showed high test-retest reliability for both the VST (r = 0.68) and the WordFAM (r = 0.82). The assessments also showed moderate convergent validity (ranging from r = 0.38 to 0.59), indicative of assessment validity. This work provides open-source English vocabulary knowledge assessments with normative data that researchers can use to foster high quality data collection in web-based environments.

Revisiting the left ear advantage for phonetic cues to talker identification.

Previous research suggests that learning to use a phonetic property [e.g., voice-onset-time, (VOT)] for talker identity supports a left ear processing advantage. Specifically, listeners trained to identify two "talkers" who only differed in characteristic VOTs showed faster talker identification for stimuli presented to the left ear compared to that presented to the right ear, which is interpreted as evidence of hemispheric lateralization consistent with task demands. Experiment 1 (n = 97) aimed to replicate this finding and identify predictors of performance; experiment 2 (n = 79) aimed to replicate this finding under conditions that better facilitate observation of laterality effects. Listeners completed a talker identification task during pretest, training, and posttest phases. Inhibition, category identification, and auditory acuity were also assessed in experiment 1. Listeners learned to use VOT for talker identity, which was positively associated with auditory acuity. Talker identification was not influenced by ear of presentation, and Bayes factors indicated strong support for the null. These results suggest that talker-specific phonetic variation is not sufficient to induce a left ear advantage for talker identification; together with the extant literature, this instead suggests that hemispheric lateralization for talker-specific phonetic variation requires phonetic variation to be conditioned on talker differences in source characteristics.

Autism attenuates the perception of the mind-body divide.

People are intuitive Dualists-they tacitly consider the mind as ethereal, distinct from the body. Here we ask whether Dualism emerges naturally from the conflicting core principles that guide reasoning about objects, on the one hand, and about the minds of agents (theory of mind, ToM), on the other. To address this question, we explore Dualist reasoning in autism spectrum disorder (ASD)-a congenital disorder known to compromise ToM. If Dualism arises from ToM, then ASD ought to attenuate Dualism and promote Physicalism. In line with this prediction, Experiment 1 shows that, compared to controls, people with ASD are more likely to view psychological traits as embodied-as likely to manifest in a replica of one's body. Experiment 2 demonstrates that, unlike controls, people with ASD do not consider thoughts as disembodied-as persistent in the afterlife (upon the body's demise). If ASD promotes the perception of the psyche as embodied, and if (per Essentialism) embodiment suggests innateness, then ASD should further promote Nativism-this bias is shown in Experiment 3. Finally, Experiment 4 demonstrates that, in neurotypical (NT) participants, difficulties with ToM correlate with Physicalism. These results are the first to show that ASD attenuates Dualist reasoning and to link Dualism to ToM. These conclusions suggest that the mind-body distinction might be natural for people to entertain.

Many tasks, same outcome: Role of training task on learning and maintenance of noise-vocoded speech.

Listeners who use cochlear implants show variability in speech recognition. Research suggests that structured auditory training can improve speech recognition outcomes in cochlear implant users, and a central goal in the rehabilitation literature is to identify factors that maximize training. Here, we examined factors that may influence perceptual learning for noise-vocoded speech in normal hearing listeners as a foundational step towards clinical recommendations. Three groups of listeners were exposed to anomalous noise-vocoded sentences and completed one of three training tasks: transcription with feedback, transcription without feedback, or talker identification. Listeners completed a word transcription test at three time points: immediately before training, immediately after training, and one week following training. Accuracy at test was indexed by keyword accuracy at the sentence-initial and sentence-final position for high and low predictability noise-vocoded sentences. Following training, listeners showed improved transcription for both sentence-initial and sentence-final items, and for both low and high predictability sentences. The training groups showed robust and equivalent learning of noise-vocoded sentences immediately after training. Critically, gains were largely maintained equivalently among training groups one week later. These results converge with evidence pointing towards the utility of non-traditional training tasks to maximize perceptual learning of noise-vocoded speech.

Perceptual learning of multiple talkers: Determinants, characteristics, and limitations.

Research suggests that listeners simultaneously update talker-specific generative models to reflect structured phonetic variation. Because past investigations exposed listeners to talkers of different genders, it is unknown whether adaptation is talker specific or rather linked to a broader sociophonetic class. Here, we test determinants of listeners' ability to update and apply talker-specific models for speech perception. In six experiments (n = 480), listeners were first exposed to the speech of two talkers who produced ambiguous fricative energy. The talkers' speech was interleaved during exposure, and lexical context differentially biased interpretation of the ambiguity as either /s/ or /ʃ/ for each talker. At test, listeners categorized tokens from ashi-asi continua, one for each talker. Across conditions and experiments, we manipulated exposure quantity, talker gender, blocked versus interleaved talker structure at test, and the degree to which fricative acoustics differed between talkers. When test was blocked by talker, learning was observed for different but not same gender talkers. When talkers were interleaved at test, learning was observed for both different and same gender talkers, which was attenuated when fricative acoustics were constant across talkers. There was no strong evidence to suggest that adaptation to multiple talkers required increased quantity of exposure beyond that required to adapt to a single talker. These results suggest that perceptual learning for speech is achieved via a mechanism that represents a context-dependent, cumulative integration of experience with speech input and identity critical constraints on listeners' ability to dynamically apply multiple generative models in mixed talker listening environments.

Context effects in perception of vowels differentiated by F1 are not influenced by variability in talkers' mean F1 or F3.

Spectral properties of earlier sounds (context) influence recognition of later sounds (target). Acoustic variability in context stimuli can disrupt this process. When mean fundamental frequencies (f0's) of preceding context sentences were highly variable across trials, shifts in target vowel categorization [due to spectral contrast effects (SCEs)] were smaller than when sentence mean f0's were less variable; when sentences were rearranged to exhibit high or low variability in mean first formant frequencies (F1) in a given block, SCE magnitudes were equivalent [Assgari, Theodore, and Stilp (2019) J. Acoust. Soc. Am. 145(3), 1443-1454]. However, since sentences were originally chosen based on variability in mean f0, stimuli underrepresented the extent to which mean F1 could vary. Here, target vowels (/ɪ/-/ɛ/) were categorized following context sentences that varied substantially in mean F1 (experiment 1) or mean F3 (experiment 2) with variability in mean f0 held constant. In experiment 1, SCE magnitudes were equivalent whether context sentences had high or low variability in mean F1; the same pattern was observed in experiment 2 for new sentences with high or low variability in mean F3. Variability in some acoustic properties (mean f0) can be more perceptually consequential than others (mean F1, mean F3), but these results may be task-dependent.

Individual Differences in Lexical Contributions to Speech Perception.

Purpose The extant literature suggests that individual differences in speech perception can be linked to broad receptive language phenotype. For example, a recent study found that individuals with a smaller receptive vocabulary showed diminished lexically guided perceptual learning compared to individuals with a larger receptive vocabulary. Here, we examined (a) whether such individual differences stem from variation in reliance on lexical information or variation in perceptual learning itself and (b) whether a relationship exists between lexical recruitment and lexically guided perceptual learning more broadly, as predicted by current models of lexically guided perceptual learning. Method In Experiment 1, adult participants (n = 70) completed measures of receptive and expressive language ability, lexical recruitment, and lexically guided perceptual learning. In Experiment 2, adult participants (n = 120) completed the same lexical recruitment and lexically guided perceptual learning tasks to provide a high-powered replication of the primary findings from Experiment 1. Results In Experiment 1, individuals with weaker receptive language ability showed increased lexical recruitment relative to individuals with higher receptive language ability; however, receptive language ability did not predict the magnitude of lexically guided perceptual learning. Moreover, the results of both experiments converged to show no evidence indicating a relationship between lexical recruitment and lexically guided perceptual learning. Conclusion The current findings suggest that (a) individuals with weaker language ability demonstrate increased reliance on lexical information for speech perception compared to those with stronger receptive language ability; (b) individuals with weaker language ability maintain an intact perceptual learning mechanism; and, (c) to the degree that the measures used here accurately capture individual differences in lexical recruitment and lexically guided perceptual learning, there is no graded relationship between these two constructs.

A second chance for a first impression: Sensitivity to cumulative input statistics for lexically guided perceptual learning.

Listeners use lexical knowledge to modify the mapping from acoustics to speech sounds, but the timecourse of experience that informs lexically guided perceptual learning is unknown. Some data suggest that learning is contingent on initial exposure to atypical productions, while other data suggest that learning reflects only the most recent exposure. Here we seek to reconcile these findings by assessing the type and timecourse of exposure that promote robust lexcially guided perceptual learning. In three experiments, listeners (n = 560) heard 20 critical productions interspersed among 200 trials during an exposure phase and then categorized items from an ashi-asi continuum in a test phase. In Experiment 1, critical productions consisted of ambiguous fricatives embedded in either /s/- or /ʃ/-biasing contexts. Learning was observed; the /s/-bias group showed more asi responses compared to the /ʃ/-bias group. In Experiment 2, listeners heard ambiguous and clear productions in a consistent context. Order and lexical bias were manipulated between-subjects, and perceptual learning occurred regardless of the order in which the clear and ambiguous productions were heard. In Experiment 3, listeners heard ambiguous fricatives in both /s/- and /ʃ/-biasing contexts. Order differed between two exposure groups, and no difference between groups was observed at test. Moreover, the results showed a monotonic decrease in learning across experiments, in line with decreasing exposure to stable lexically biasing contexts, and were replicated across novel stimulus sets. In contrast to previous findings showing that either initial or most recent experience are critical for lexically guided perceptual learning, the current results suggest that perceptual learning reflects cumulative experience with a talker's input over time.

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition.

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.

Talker normalization is mediated by structured indexical information.

Speech perception is challenged by indexical variability. A litany of studies on talker normalization have demonstrated that hearing multiple talkers incurs processing costs (e.g., lower accuracy, increased response time) compared to hearing a single talker. However, when reframing these studies in terms of stimulus structure, it is evident that past tests of multiple-talker (i.e., low structure) and single-talker (i.e., high structure) conditions are not representative of the graded nature of indexical variation in the environment. Here we tested the hypothesis that processing costs incurred by multiple-talker conditions would abate given increased stimulus structure. We tested this hypothesis by manipulating the degree to which talkers' voices differed acoustically (Experiment 1) and also the frequency with which talkers' voices changed (Experiment 2) in multiple-talker conditions. Listeners performed a speeded classification task for words containing vowels that varied in acoustic-phonemic ambiguity. In Experiment 1, response times progressively decreased as acoustic variability among talkers' voices decreased. In Experiment 2, blocking talkers within mixed-talker conditions led to more similar response times among single-talker and multiple-talker conditions. Neither result interacted with acoustic-phonemic ambiguity of the target vowels. Thus, the results showed that indexical structure mediated the processing costs incurred by hearing different talkers. This is consistent with the Efficient Coding Hypothesis, which proposes that sensory and perceptual processing are facilitated by stimulus structure. Defining the roles and limits of stimulus structure on speech perception is an important direction for future research.

Individual Differences in Distributional Learning for Speech: What's Ideal for Ideal Observers?

Purpose Speech perception is facilitated by listeners' ability to dynamically modify the mapping to speech sounds given systematic variation in speech input. For example, the degree to which listeners show categorical perception of speech input changes as a function of distributional variability in the input, with perception becoming less categorical as the input, becomes more variable. Here, we test the hypothesis that higher level receptive language ability is linked to the ability to adapt to low-level distributional cues in speech input. Method Listeners (n = 58) completed a distributional learning task consisting of 2 blocks of phonetic categorization for words beginning with /g/ and /k/. In 1 block, the distributions of voice onset time values specifying /g/ and /k/ had narrow variances (i.e., minimal variability). In the other block, the distributions of voice onset times specifying /g/ and /k/ had wider variances (i.e., increased variability). In addition, all listeners completed an assessment battery for receptive language, nonverbal intelligence, and reading fluency. Results As predicted by an ideal observer computational framework, the participants in aggregate showed identification responses that were more categorical for consistent compared to inconsistent input, indicative of distributional learning. However, the magnitude of learning across participants showed wide individual variability, which was predicted by receptive language ability but not by nonverbal intelligence or by reading fluency. Conclusion The results suggest that individual differences in distributional learning for speech are linked, at least in part, to receptive language ability, reflecting a decreased ability among those with weaker receptive language to capitalize on consistent input distributions.

Structured phonetic variation facilitates talker identification.

Listeners use talker-specific phonetic structure to facilitate language comprehension. This study tests whether sensitivity to talker-specific phonetic variation also facilitates talker identification. During training, two listener groups learned to associate talkers' voices with cartoon pseudo-faces. For one group, each talker produced characteristically different voice-onset-time values; for the other group, no talker-specific phonetic structure was present. After training, listeners were tested on talker identification for trained and novel words, which was improved for those who heard structured phonetic variation compared to those who did not. These findings suggest an additive benefit of talker-specific phonetic variation for talker identification beyond traditional indexical cues.