Merging information in speech recognition: feedback is never necessary

Phonetic categorization in phonological lexical neighborhoods: Facilitatory and inhibitory effects

Phonetic processing, whereby the bottom-up speech signal is translated into higher-level phonological representations such as phonemes, has been demonstrated to be influenced by phonological lexical neighborhoods. Previous studies show facilitatory effects of lexicality and phonological neighborhood density on phonetic categorization. However, given the evidence for lexical competition in spoken word recognition, we hypothesize that there are concurrent facilitatory and inhibitory effects of phonological lexical neighborhoods on phonetic processing. In Experiments 1 and 2, participants categorized the onset phoneme in word-nonword and nonword-word acoustic continua. The results show that the target word of the continuum exhibits facilitatory lexical influences whereas rhyme neighbors inhibit phonetic categorization. The results support the hypothesis that sublexical phonetic processing is affected by multiple facilitatory and inhibitory lexical forces in the processing stream.

Do They Know It's Christmash? Lexical Knowledge Directly Impacts Speech Perception

We recently reported strong, replicable (i.e., replicated) evidence for lexically mediated compensation for coarticulation (LCfC; Luthra et al., 2021), whereby lexical knowledge influences a prelexical process. Critically, evidence for LCfC provides robust support for interactive models of cognition that include top-down feedback and is inconsistent with autonomous models that allow only feedforward processing. McQueen, Jesse, and Mitterer (2023) offer five counter-arguments against our interpretation; we respond to each of those arguments here and conclude that top-down feedback provides the most parsimonious explanation of extant data.

Lexical Feedback in the Time-Invariant String Kernel (TISK) Model of Spoken Word Recognition

The Time-Invariant String Kernel (TISK) model of spoken word recognition (Hannagan, Magnuson & Grainger, 2013; You & Magnuson, 2018) is an interactive activation model with many similarities to TRACE (McClelland & Elman, 1986). However, by replacing most time-specific nodes in TRACE with time-invariant open-diphone nodes, TISK uses orders of magnitude fewer nodes and connections than TRACE. Although TISK performed remarkably similarly to TRACE in simulations reported by Hannagan et al., the original TISK implementation did not include lexical feedback, precluding simulation of top-down effects, and leaving open the possibility that adding feedback to TISK might fundamentally alter its performance. Here, we demonstrate that when lexical feedback is added to TISK, it gains the ability to simulate top-down effects without losing the ability to simulate the fundamental phenomena tested by Hannagan et al. Furthermore, with feedback, TISK demonstrates graceful degradation when noise is added to input, although parameters can be found that also promote (less) graceful degradation without feedback. We review arguments for and against feedback in cognitive architectures, and conclude that feedback provides a computationally efficient basis for robust constraint-based processing.

Sandhi-based predictability of pitch accent facilitates word recognition in Kansai Japanese speakers

This study investigates the predictability effects of pitch accent on word recognition using the sandhi rule in Kansai Japanese (KJ). Native KJ speakers and native Tokyo Japanese (TJ) speakers (control group) saw images of four objects while hearing modifier + noun phrases and selected the corresponding image as quickly as possible. The word-initial tone of the noun's initial mora was predictable or unpredictable based on the tone of the preceding modifier's final mora in KJ but not in TJ. Experiment 1 found faster reaction times in the predictable conditions compared with the unpredictable conditions in KJ speakers but only when the modifier had an all-low tone sequence. This finding suggests that a modifier-ending that changes following the sandhi rule can function as a reliable cue to constrain an upcoming tone, whereas a modifier-ending tone that remains the same as in the citation form cannot (although the next tone is predictable). Unexpectedly, we found the same effect, albeit weaker, in TJ speakers. Experiment 2 replicated this effect and additionally showed that the facilitation effect was not due to TJ speakers having sufficient exposure to KJ to be familiar with the KJ sandhi rule. We speculate that the effect in TJ speakers is related to a language universal constraint against a sequence of low tones without a high tone within a phonological word, which may urge listeners to listen for a high tone in the upcoming input.

Disentangling the Role of Biphone Probability From Neighborhood Density in the Perception of Nonwords

In six experiments we explored how biphone probability and lexical neighborhood density influence listeners' categorization of vowels embedded in nonword sequences. We found independent effects of each. Listeners shifted categorization of a phonetic continuum to create a higher probability sequence, even when neighborhood density was controlled. Similarly, listeners shifted categorization to create a nonword from a denser neighborhood, even when biphone probability was controlled. Next, using a visual world eye-tracking task, we determined that biphone probability information is used rapidly by listeners in perception. In contrast, task complexity and irrelevant variability in the stimuli interfere with neighborhood density effects. These results support a model in which both biphone probability and neighborhood density independently affect word recognition, but only biphone probability effects are observed early in processing.

Why are listeners hindered by talker variability?

Though listeners readily recognize speech from a variety of talkers, accommodating talker variability comes at a cost: Myriad studies have shown that listeners are slower to recognize a spoken word when there is talker variability compared with when talker is held constant. This review focuses on two possible theoretical mechanisms for the emergence of these processing penalties. One view is that multitalker processing costs arise through a resource-demanding talker accommodation process, wherein listeners compare sensory representations against hypothesized perceptual candidates and error signals are used to adjust the acoustic-to-phonetic mapping (an active control process known as contextual tuning). An alternative proposal is that these processing costs arise because talker changes involve salient stimulus-level discontinuities that disrupt auditory attention. Some recent data suggest that multitalker processing costs may be driven by both mechanisms operating over different time scales. Fully evaluating this claim requires a foundational understanding of both talker accommodation and auditory streaming; this article provides a primer on each literature and also reviews several studies that have observed multitalker processing costs. The review closes by underscoring a need for comprehensive theories of speech perception that better integrate auditory attention and by highlighting important considerations for future research in this area.

Reaction time for correct identification of vowels in consonant-vowel syllables and of vowel segments

Reaction times for correct vowel identification were measured to determine the effects of intertrial intervals, vowel, and cue type. Thirteen adults with normal hearing, aged 20-38 years old, participated. Stimuli included three naturally produced syllables (/ba/ /bi/ /bu/) presented whole or segmented to isolate the formant transition or static formant center. Participants identified the vowel presented via loudspeaker by mouse click. Results showed a significant effect of intertrial intervals, no significant effect of cue type, and a significant vowel effect-suggesting that feedback occurs, vowel identification may depend on cue duration, and vowel bias may stem from focal structure.

Contra assertions, feedback improves word recognition: How feedback and lateral inhibition sharpen signals over noise

Whether top-down feedback modulates perception has deep implications for cognitive theories. Debate has been vigorous in the domain of spoken word recognition, where competing computational models and agreement on at least one diagnostic experimental paradigm suggest that the debate may eventually be resolvable. Norris and Cutler (2021) revisit arguments against lexical feedback in spoken word recognition models. They also incorrectly claim that recent computational demonstrations that feedback promotes accuracy and speed under noise (Magnuson et al., 2018) were due to the use of the Luce choice rule rather than adding noise to inputs (noise was in fact added directly to inputs). They also claim that feedback cannot improve word recognition because feedback cannot distinguish signal from noise. We have two goals in this paper. First, we correct the record about the simulations of Magnuson et al. (2018). Second, we explain how interactive activation models selectively sharpen signals via joint effects of feedback and lateral inhibition that boost lexically-coherent sublexical patterns over noise. We also review a growing body of behavioral and neural results consistent with feedback and inconsistent with autonomous (non-feedback) architectures, and conclude that parsimony supports feedback. We close by discussing the potential for synergy between autonomous and interactive approaches.

Short-term exposure alters adult listeners' perception of segmental phonotactics

This study evaluates the malleability of adults' perception of probabilistic phonotactic (biphone) probabilities, building on a body of literature on statistical phonotactic learning. It was first replicated that listeners categorize phonetic continua as sounds that create higher-probability sequences in their native language. Listeners were also exposed to skewed distributions of biphone contexts, which resulted in the enhancement or reversal of these effects. Thus, listeners dynamically update biphone probabilities (BPs) and bring this to bear on perception of ambiguous acoustic information. These effects can override long-term BP effects rooted in native language experience.

An eye on semantics: a study on the influence of concreteness and predictability on early fixation durations

We used eye-tracking during natural reading to study how semantic control and representation mechanisms interact for the successful comprehension of sentences, by manipulating sentence context and single-word meaning. Specifically, we examined whether a word's semantic characteristic (concreteness) affects first fixation and gaze durations (FFDs and GDs) and whether it interacts with the predictability of a word. We used a linear mixed effects model including several possible psycholinguistic covariates. We found a small but reliable main effect of concreteness and replicated a predictability effect on FFDs, but we found no interaction between the two. The results parallel previous findings of additive effects of predictability (context) and frequency (lexical level) in fixation times. Our findings suggest that the semantics of a word and the context created by the preceding words additively influence early stages of word processing in natural sentence reading.

Assessing the size of non-Māori-speakers' active Māori lexicon

Most non-Māori-speaking New Zealanders are regularly exposed to Māori throughout their lives without seeming to build any extensive Māori lexicon; at best, they know a small number of words which are frequently used and sometimes borrowed into English. Here, we ask how many Māori words non-Māori-speaking New Zealanders know, in two ways: how many can they identify as real Māori words, and how many can they actively define? We show that non-Māori-speaking New Zealanders can readily identify many more Māori words than they can define, and that the number of words they can reliably define is quite small. This result adds crucial support to the idea presented in earlier work that non-Māori-speaking New Zealanders have implicit form-based (proto-lexical) knowledge of many Māori words, but explicit semantic (lexical) knowledge of few. Building on this distinction, we further ask how different levels of word knowledge modulate effects of phonotactic probability on the accessing of that knowledge, across both tasks and participants. We show that participants' implicit word knowledge leads to effects of phonotactic probability-and related effects of neighbourhood density-in a word/non-word discrimination task, but not in a more explicit task that requires the active definition of words. Similarly, we show that the effects of phonotactic probability on word/non-word discrimination are strong among participants who appear to lack explicit word knowledge, as indicated by their weak discrimination performance, but absent among participants who appear to have explicit word knowledge, as indicated by their strong discrimination performance. Together, these results suggest that phonotactic probability plays its strongest roles in the absence of explicit semantic knowledge.

Recognizing non-native spoken words in background noise increases interference from the native language

Listeners frequently recognize spoken words in the presence of background noise. Previous research has shown that noise reduces phoneme intelligibility and hampers spoken-word recognition - especially for non-native listeners. In the present study, we investigated how noise influences lexical competition in both the non-native and the native language, reflecting the degree to which both languages are co-activated. We recorded the eye movements of native Dutch participants as they listened to English sentences containing a target word while looking at displays containing four objects. On target-present trials, the visual referent depicting the target word was present, along with three unrelated distractors. On target-absent trials, the target object (e.g., wizard) was absent. Instead, the display contained an English competitor, overlapping with the English target in phonological onset (e.g., window), a Dutch competitor, overlapping with the English target in phonological onset (e.g., wimpel, pennant), and two unrelated distractors. Half of the sentences was masked by speech-shaped noise; the other half was presented in quiet. Compared to speech in quiet, noise delayed fixations to the target objects on target-present trials. For target-absent trials, we observed that the likelihood for fixation biases towards the English and Dutch onset competitors (over the unrelated distractors) was larger in noise than in quiet. Our data thus show that the presence of background noise increases lexical competition in the task-relevant non-native (English) and in the task-irrelevant native (Dutch) language. The latter reflects stronger interference of one's native language during non-native spoken-word recognition under adverse conditions.

The effect of topic familiarity and volatility of auditory scene on selective auditory attention

Selective auditory attention has been shown to modulate the cortical representation of speech. This effect has been well documented in acoustically more challenging environments. However, the influence of top-down factors, in particular topic familiarity, on this process remains unclear, despite evidence that semantic information can promote speech-in-noise perception. Apart from individual features forming a static listening condition, dynamic and irregular changes of auditory scenes-volatile listening environments-have been less studied. To address these gaps, we explored the influence of topic familiarity and volatile listening on the selective auditory attention process during dichotic listening using electroencephalography. When stories with unfamiliar topics were presented, participants' comprehension was severely degraded. However, their cortical activity selectively tracked the speech of the target story well. This implies that topic familiarity hardly influences the speech tracking neural index, possibly when the bottom-up information is sufficient. However, when the listening environment was volatile and the listeners had to re-engage in new speech whenever auditory scenes altered, the neural correlates of the attended speech were degraded. In particular, the cortical response to the attended speech and the spatial asymmetry of the response to the left and right attention were significantly attenuated around 100-200 ms after the speech onset. These findings suggest that volatile listening environments could adversely affect the modulation effect of selective attention, possibly by hampering proper attention due to increased perceptual load.

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.

Selective adaptation of German /r/: A role for perceptual saliency

In three experiments, we examined selective adaptation of German /r/ depending on the positional and allophonic overlap between adaptors and targets. A previous study had shown that selective adaptation effects with /r/ in Dutch require allophonic overlap between adaptor and target. We aimed at replicating this finding in German, which also has many allophones of /r/. German post-vocalic /r/ is often vocalized, and pre-vocalic /r/ can occur in at least three forms: uvular fricative [ʁ], uvular trill [ʀ] and alveolar trill [r]. We tested selective adaptation between these variants. The critical questions were whether an allophonic overlap is necessary for adaptation or whether phonemic overlap is sufficient to generate an adaptation effect. Surprisingly, our results show that both assertations are wrong: Adaptation does not require an allophonic overlap between adaptors and target and neither is phonemic overlap sufficient. Even more surprisingly, trilled adaptors led to more adaptation for a uvular-fricative target than uvular-fricative adaptors themselves. We suggest that the perceptual salience of the adaptors may be a hitherto underestimated influence on selective adaptation.

Developmental change in children's speech processing of auditory and visual cues: An eyetracking study

This study investigates how children aged two to eight years (N = 129) and adults (N = 29) use auditory and visual speech for word recognition. The goal was to bridge the gap between apparent successes of visual speech processing in young children in visual-looking tasks, with apparent difficulties of speech processing in older children from explicit behavioural measures. Participants were presented with familiar words in audio-visual (AV), audio-only (A-only) or visual-only (V-only) speech modalities, then presented with target and distractor images, and looking to targets was measured. Adults showed high accuracy, with slightly less target-image looking in the V-only modality. Developmentally, looking was above chance for both AV and A-only modalities, but not in the V-only modality until 6 years of age (earlier on /k/-initial words). Flexible use of visual cues for lexical access develops throughout childhood.

Don't force it! Gradient speech categorization calls for continuous categorization tasks

Research on speech categorization and phoneme recognition has relied heavily on tasks in which participants listen to stimuli from a speech continuum and are asked to either classify each stimulus (identification) or discriminate between them (discrimination). Such tasks rest on assumptions about how perception maps onto discrete responses that have not been thoroughly investigated. Here, we identify critical challenges in the link between these tasks and theories of speech categorization. In particular, we show that patterns that have traditionally been linked to categorical perception could arise despite continuous underlying perception and that patterns that run counter to categorical perception could arise despite underlying categorical perception. We describe an alternative measure of speech perception using a visual analog scale that better differentiates between processes at play in speech categorization, and we review some recent findings that show how this task can be used to better inform our theories.

Sketching the Landscape of Speech Perception Research (2000-2020): A Bibliometric Study

Based on 6,407 speech perception research articles published between 2000 and 2020, a bibliometric analysis was conducted to identify leading countries, research institutes, researchers, research collaboration networks, high impact research articles, central research themes and trends in speech perception research. Analysis of highly cited articles and researchers indicated three foundational theoretical approaches to speech perception, that is the motor theory, the direct realism and the computational approach as well as four non-native speech perception models, that is the Speech Learning Model, the Perceptual Assimilation Model, the Native Language Magnet model, and the Second Language Linguistic Perception model. Citation networks, term frequency analysis and co-word networks revealed several central research topics: audio-visual speech perception, spoken word recognition, bilingual and infant/child speech perception and learning. Two directions for future research were also identified: (1) speech perception by clinical populations, such as hearing loss children with cochlear implants and speech perception across lifespan, including infants and aged population; (2) application of neurocognitive techniques in investigating activation of different brain regions during speech perception. Our bibliometric analysis can facilitate research advancements and future collaborations among linguists, psychologists and brain scientists by offering a bird view of this interdisciplinary field.

Bengali nasal vowels: lexical representation and listener perception

This paper focuses on the question of the representation of nasality as well as speakers' awareness and perceptual use of phonetic nasalisation by examining surface nasalisation in two types of vowels in Bengali: underlying nasal vowels (CṼC) and nasalised vowels before a nasal consonant (CVN). A series of three cross-modal forced-choice experiments was used to investigate the hypothesis that only unpredictable nasalisation is stored and that this sparse representation governs how listeners interpret vowel nasality. Visual full-word targets were preceded by auditory primes consisting of CV segments of CVC words with nasal vowels ([tʃɑ̃] for [tʃɑ̃d] 'moon'), oral vowels ([tʃɑ] for [tʃɑl] 'unboiled rice') or nasalised oral vowels ([tʃɑ̃(n)] for [tʃɑ̃n] 'bath') and reaction times and errors were measured. Some targets fully matched the prime while some matched surface or underlying representation only. Faster reaction times and fewer errors were observed after CṼC primes compared to both CVC and CVN primes. Furthermore, any surface nasality was most frequently matched to a CṼC target unless no such target was available. Both reaction times and error data indicate that nasal vowels are specified for nasality leading to faster recognition compared to underspecified oral vowels, which cannot be perfectly matched with incoming signals.

Parallel processing in speech perception with local and global representations of linguistic context

Speech processing is highly incremental. It is widely accepted that human listeners continuously use the linguistic context to anticipate upcoming concepts, words, and phonemes. However, previous evidence supports two seemingly contradictory models of how a predictive context is integrated with the bottom-up sensory input: Classic psycholinguistic paradigms suggest a two-stage process, in which acoustic input initially leads to local, context-independent representations, which are then quickly integrated with contextual constraints. This contrasts with the view that the brain constructs a single coherent, unified interpretation of the input, which fully integrates available information across representational hierarchies, and thus uses contextual constraints to modulate even the earliest sensory representations. To distinguish these hypotheses, we tested magnetoencephalography responses to continuous narrative speech for signatures of local and unified predictive models. Results provide evidence that listeners employ both types of models in parallel. Two local context models uniquely predict some part of early neural responses, one based on sublexical phoneme sequences, and one based on the phonemes in the current word alone; at the same time, even early responses to phonemes also reflect a unified model that incorporates sentence-level constraints to predict upcoming phonemes. Neural source localization places the anatomical origins of the different predictive models in nonidentical parts of the superior temporal lobes bilaterally, with the right hemisphere showing a relative preference for more local models. These results suggest that speech processing recruits both local and unified predictive models in parallel, reconciling previous disparate findings. Parallel models might make the perceptual system more robust, facilitate processing of unexpected inputs, and serve a function in language acquisition.

What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach

Cognitive network science is an emerging approach that uses the mathematical tools of network science to map the relationships among representations stored in memory to examine how that structure might influence processing. In the present study, we used computer simulations to compare the ability of a well-known model of spoken word recognition, TRACE, to the ability of a cognitive network model with a spreading activation-like process to account for the findings from several previously published behavioral studies of language processing. In all four simulations, the TRACE model failed to retrieve a sufficient number of words to assess if it could replicate the behavioral findings. The cognitive network model successfully replicated the behavioral findings in Simulations 1 and 2. However, in Simulation 3a, the cognitive network did not replicate the behavioral findings, perhaps because an additional mechanism was not implemented in the model. However, in Simulation 3b, when the decay parameter in spreadr was manipulated to model this mechanism the cognitive network model successfully replicated the behavioral findings. The results suggest that models of cognition need to take into account the multi-scale structure that exists among representations in memory, and how that structure can influence processing.

Idiosyncratic use of bottom-up and top-down information leads to differences in speech perception flexibility: Converging evidence from ERPs and eye-tracking

Listeners generally categorize speech sounds in a gradient manner. However, recent work, using a visual analogue scaling (VAS) task, suggests that some listeners show more categorical performance, leading to less flexible cue integration and poorer recovery from misperceptions (Kapnoula et al., 2017, 2021). We asked how individual differences in speech gradiency can be reconciled with the well-established gradiency in the modal listener, showing how VAS performance relates to both Visual World Paradigm and EEG measures of gradiency. We also investigated three potential sources of these individual differences: inhibitory control; lexical inhibition; and early cue encoding. We used the N1 ERP component to track pre-categorical encoding of Voice Onset Time (VOT). The N1 linearly tracked VOT, reflecting a fundamentally gradient speech perception; however, for less gradient listeners, this linearity was disrupted near the boundary. Thus, while all listeners are gradient, they may show idiosyncratic encoding of specific cues, affecting downstream processing.

Speech Computations of the Human Superior Temporal Gyrus

Human speech perception results from neural computations that transform external acoustic speech signals into internal representations of words. The superior temporal gyrus (STG) contains the nonprimary auditory cortex and is a critical locus for phonological processing. Here, we describe how speech sound representation in the STG relies on fundamentally nonlinear and dynamical processes, such as categorization, normalization, contextual restoration, and the extraction of temporal structure. A spatial mosaic of local cortical sites on the STG exhibits complex auditory encoding for distinct acoustic-phonetic and prosodic features. We propose that as a population ensemble, these distributed patterns of neural activity give rise to abstract, higher-order phonemic and syllabic representations that support speech perception. This review presents a multi-scale, recurrent model of phonological processing in the STG, highlighting the critical interface between auditory and language systems. Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The Effect of Orthographic Transparency on Auditory Word Recognition Across the Development of Reading Proficiency

A question under debate in psycholinguistics is the nature of the relationship between spoken and written languages. Although it has been extensively shown that orthographic transparency, which varies across writing systems, strongly affects reading performance, its role in speech processing is much less investigated. The present study addressed this issue in Persian, whose writing system provides a possibility to assess the impact of orthographic transparency on spoken word recognition in young children at different stages of reading acquisition. In Persian, the long vowels are systematically present in the script, whereas the spelling correspondence of short vowels is progressively omitted from the script in the course of reading acquisition, thus, turning transparent into opaque spelling. Based on this unique characteristic, we tested 144 monolingual Persian-speaking nonreaders (i.e., preschoolers) and readers (second graders to fifth graders and young adults) in an auditory lexical decision task using transparent and opaque words. Overall, the results showed that, in accordance with the fact that the diacritics of short vowels are progressively omitted during the second year of schooling, the stimuli containing short vowels (opaque words) were recognized more slowly than transparent ones in third graders. Interestingly, there is a hint that the emergence of the transparency effect in the third graders was associated with an overall slower recognition speed in this group compared to their younger peers. These findings indicate that learning opaque spelling-sound correspondence might not only generate interference between the two language codes but also induce a general processing cost in the entire spoken language system.

Statistical learning and prosodic bootstrapping differentially affect neural synchronization during speech segmentation

Neural oscillations constitute an intrinsic property of functional brain organization that facilitates the tracking of linguistic units at multiple time scales through brain-to-stimulus alignment. This ubiquitous neural principle has been shown to facilitate speech segmentation and word learning based on statistical regularities. However, there is no common agreement yet on whether speech segmentation is mediated by a transition of neural synchronization from syllable to word rate, or whether the two time scales are concurrently tracked. Furthermore, it is currently unknown whether syllable transition probability contributes to speech segmentation when lexical stress cues can be directly used to extract word forms. Using Inter-Trial Coherence (ITC) analyses in combinations with Event-Related Potentials (ERPs), we showed that speech segmentation based on both statistical regularities and lexical stress cues was accompanied by concurrent neural synchronization to syllables and words. In particular, ITC at the word rate was generally higher in structured compared to random sequences, and this effect was particularly pronounced in the flat condition. Furthermore, ITC at the syllable rate dynamically increased across the blocks of the flat condition, whereas a similar modulation was not observed in the stressed condition. Notably, in the flat condition ITC at both time scales correlated with each other, and changes in neural synchronization were accompanied by a rapid reconfiguration of the P200 and N400 components with a close relationship between ITC and ERPs. These results highlight distinct computational principles governing neural synchronization to pertinent linguistic units while segmenting speech under different listening conditions.

What Can Network Science Tell Us About Phonology and Language Processing?

Contemporary psycholinguistic models place significant emphasis on the cognitive processes involved in the acquisition, recognition, and production of language but neglect many issues related to the representation of language‐related information in the mental lexicon. In contrast, a central tenet of network science is that the structure of a network influences the processes that operate in that system, making process and representation inextricably connected. Here, we consider how the structure found across phonological networks of several languages from different language families may influence language processing as we age and experience diseases that affect cognition during the typical and atypical acquisition of new words, during typical perception and production of speech in adults, and during language change over time. We conclude that the network science approach may not only provide insights into specific language processes but also provide a way to connect the work from these domains, which are becoming increasingly balkanized.

Robust Lexically Mediated Compensation for Coarticulation: Christmash Time Is Here Again

A long-standing question in cognitive science is how high-level knowledge is integrated with sensory input. For example, listeners can leverage lexical knowledge to interpret an ambiguous speech sound, but do such effects reflect direct top-down influences on perception or merely postperceptual biases? A critical test case in the domain of spoken word recognition is lexically mediated compensation for coarticulation (LCfC). Previous LCfC studies have shown that a lexically restored context phoneme (e.g., /s/ in Christma#) can alter the perceived place of articulation of a subsequent target phoneme (e.g., the initial phoneme of a stimulus from a tapes-capes continuum), consistent with the influence of an unambiguous context phoneme in the same position. Because this phoneme-to-phoneme compensation for coarticulation is considered sublexical, scientists agree that evidence for LCfC would constitute strong support for top-down interaction. However, results from previous LCfC studies have been inconsistent, and positive effects have often been small. Here, we conducted extensive piloting of stimuli prior to testing for LCfC. Specifically, we ensured that context items elicited robust phoneme restoration (e.g., that the final phoneme of Christma# was reliably identified as /s/) and that unambiguous context-final segments (e.g., a clear /s/ at the end of Christmas) drove reliable compensation for coarticulation for a subsequent target phoneme. We observed robust LCfC in a well-powered, preregistered experiment with these pretested items (N = 40) as well as in a direct replication study (N = 40). These results provide strong evidence in favor of computational models of spoken word recognition that include top-down feedback.

More why, less how: What we need from models of cognition

Science regularly experiences periods in which simply describing the world is prioritised over attempting to explain it. Cognition, this journal, came into being some 45 years ago as an attempt to lay one such period to rest; without doubt, it has helped create the current cognitive science climate in which theory is decidedly welcome. Here we summarise the reasons why a theoretical approach is imperative in our field, and call attention to some potentially counter-productive trends in which cognitive models are concerned too exclusively with how processes work at the expense of why the processes exist in the first place and thus what the goal of modelling them must be.

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We suggest that theories should try to explain ‘why’ not just ‘how’.

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We reinforce Darwin’s (1861) point that “All [scientific] observation must be for or against some view if it is to be of [scientific] service!”.

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Jacques Mehler and Cognition revitalised theory in cognitive psychology.

Data-driven machine learning models for decoding speech categorization from evoked brain responses

Objective.Categorical perception (CP) of audio is critical to understand how the human brain perceives speech sounds despite widespread variability in acoustic properties. Here, we investigated the spatiotemporal characteristics of auditory neural activity that reflects CP for speech (i.e. differentiates phonetic prototypes from ambiguous speech sounds).Approach.We recorded 64-channel electroencephalograms as listeners rapidly classified vowel sounds along an acoustic-phonetic continuum. We used support vector machine classifiers and stability selection to determine when and where in the brain CP was best decoded across space and time via source-level analysis of the event-related potentials.Main results. We found that early (120 ms) whole-brain data decoded speech categories (i.e. prototypical vs. ambiguous tokens) with 95.16% accuracy (area under the curve 95.14%;F1-score 95.00%). Separate analyses on left hemisphere (LH) and right hemisphere (RH) responses showed that LH decoding was more accurate and earlier than RH (89.03% vs. 86.45% accuracy; 140 ms vs. 200 ms). Stability (feature) selection identified 13 regions of interest (ROIs) out of 68 brain regions [including auditory cortex, supramarginal gyrus, and inferior frontal gyrus (IFG)] that showed categorical representation during stimulus encoding (0-260 ms). In contrast, 15 ROIs (including fronto-parietal regions, IFG, motor cortex) were necessary to describe later decision stages (later 300-800 ms) of categorization but these areas were highly associated with the strength of listeners' categorical hearing (i.e. slope of behavioral identification functions).Significance.Our data-driven multivariate models demonstrate that abstract categories emerge surprisingly early (∼120 ms) in the time course of speech processing and are dominated by engagement of a relatively compact fronto-temporal-parietal brain network.

Data-driven machine learning models for decoding speech categorization from evoked brain responses

Objective.Categorical perception (CP) of audio is critical to understand how the human brain perceives speech sounds despite widespread variability in acoustic properties. Here, we investigated the spatiotemporal characteristics of auditory neural activity that reflects CP for speech (i.e. differentiates phonetic prototypes from ambiguous speech sounds).Approach.We recorded 64-channel electroencephalograms as listeners rapidly classified vowel sounds along an acoustic-phonetic continuum. We used support vector machine classifiers and stability selection to determine when and where in the brain CP was best decoded across space and time via source-level analysis of the event-related potentials.Main results. We found that early (120 ms) whole-brain data decoded speech categories (i.e. prototypical vs. ambiguous tokens) with 95.16% accuracy (area under the curve 95.14%;F1-score 95.00%). Separate analyses on left hemisphere (LH) and right hemisphere (RH) responses showed that LH decoding was more accurate and earlier than RH (89.03% vs. 86.45% accuracy; 140 ms vs. 200 ms). Stability (feature) selection identified 13 regions of interest (ROIs) out of 68 brain regions [including auditory cortex, supramarginal gyrus, and inferior frontal gyrus (IFG)] that showed categorical representation during stimulus encoding (0-260 ms). In contrast, 15 ROIs (including fronto-parietal regions, IFG, motor cortex) were necessary to describe later decision stages (later 300-800 ms) of categorization but these areas were highly associated with the strength of listeners' categorical hearing (i.e. slope of behavioral identification functions).Significance.Our data-driven multivariate models demonstrate that abstract categories emerge surprisingly early (∼120 ms) in the time course of speech processing and are dominated by engagement of a relatively compact fronto-temporal-parietal brain network.

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.

The Learning Signal in Perceptual Tuning of Speech: Bottom Up Versus Top-Down Information

Cognitive systems face a tension between stability and plasticity. The maintenance of long-term representations that reflect the global regularities of the environment is often at odds with pressure to flexibly adjust to short-term input regularities that may deviate from the norm. This tension is abundantly clear in speech communication when talkers with accents or dialects produce input that deviates from a listener's language community norms. Prior research demonstrates that when bottom-up acoustic information or top-down word knowledge is available to disambiguate speech input, there is short-term adaptive plasticity such that subsequent speech perception is shifted even in the absence of the disambiguating information. Although such effects are well-documented, it is not yet known whether bottom-up and top-down resolution of ambiguity may operate through common processes, or how these information sources may interact in guiding the adaptive plasticity of speech perception. The present study investigates the joint contributions of bottom-up information from the acoustic signal and top-down information from lexical knowledge in the adaptive plasticity of speech categorization according to short-term input regularities. The results implicate speech category activation, whether from top-down or bottom-up sources, in driving rapid adjustment of listeners' reliance on acoustic dimensions in speech categorization. Broadly, this pattern of perception is consistent with dynamic mapping of input to category representations that is flexibly tuned according to interactive processing accommodating both lexical knowledge and idiosyncrasies of the acoustic input.

Auditory cortex is susceptible to lexical influence as revealed by informational vs. energetic masking of speech categorization

Speech perception requires the grouping of acoustic information into meaningful phonetic units via the process of categorical perception (CP). Environmental masking influences speech perception and CP. However, it remains unclear at which stage of processing (encoding, decision, or both) masking affects listeners' categorization of speech signals. The purpose of this study was to determine whether linguistic interference influences the early acoustic-phonetic conversion process inherent to CP. To this end, we measured source level, event related brain potentials (ERPs) from auditory cortex (AC) and inferior frontal gyrus (IFG) as listeners rapidly categorized speech sounds along a /da/ to /ga/ continuum presented in three listening conditions: quiet, and in the presence of forward (informational masker) and time-reversed (energetic masker) 2-talker babble noise. Maskers were matched in overall SNR and spectral content and thus varied only in their degree of linguistic interference (i.e., informational masking). We hypothesized a differential effect of informational versus energetic masking on behavioral and neural categorization responses, where we predicted increased activation of frontal regions when disambiguating speech from noise, especially during lexical-informational maskers. We found (1) informational masking weakens behavioral speech phoneme identification above and beyond energetic masking; (2) low-level AC activity not only codes speech categories but is susceptible to higher-order lexical interference; (3) identifying speech amidst noise recruits a cross hemispheric circuit (AC_left → IFG_right) whose engagement varies according to task difficulty. These findings provide corroborating evidence for top-down influences on the early acoustic-phonetic analysis of speech through a coordinated interplay between frontotemporal brain areas.

Top-Down Inference in the Auditory System: Potential Roles for Corticofugal Projections

It has become widely accepted that humans use contextual information to infer the meaning of ambiguous acoustic signals. In speech, for example, high-level semantic, syntactic, or lexical information shape our understanding of a phoneme buried in noise. Most current theories to explain this phenomenon rely on hierarchical predictive coding models involving a set of Bayesian priors emanating from high-level brain regions (e.g., prefrontal cortex) that are used to influence processing at lower-levels of the cortical sensory hierarchy (e.g., auditory cortex). As such, virtually all proposed models to explain top-down facilitation are focused on intracortical connections, and consequently, subcortical nuclei have scarcely been discussed in this context. However, subcortical auditory nuclei receive massive, heterogeneous, and cascading descending projections at every level of the sensory hierarchy, and activation of these systems has been shown to improve speech recognition. It is not yet clear whether or how top-down modulation to resolve ambiguous sounds calls upon these corticofugal projections. Here, we review the literature on top-down modulation in the auditory system, primarily focused on humans and cortical imaging/recording methods, and attempt to relate these findings to a growing animal literature, which has primarily been focused on corticofugal projections. We argue that corticofugal pathways contain the requisite circuitry to implement predictive coding mechanisms to facilitate perception of complex sounds and that top-down modulation at early (i.e., subcortical) stages of processing complement modulation at later (i.e., cortical) stages of processing. Finally, we suggest experimental approaches for future studies on this topic.

Lexical Influences on Categorical Speech Perception Are Driven by a Temporoparietal Circuit

Categorical judgments of otherwise identical phonemes are biased toward hearing words (i.e., "Ganong effect") suggesting lexical context influences perception of even basic speech primitives. Lexical biasing could manifest via late stage postperceptual mechanisms related to decision or, alternatively, top-down linguistic inference that acts on early perceptual coding. Here, we exploited the temporal sensitivity of EEG to resolve the spatiotemporal dynamics of these context-related influences on speech categorization. Listeners rapidly classified sounds from a /gɪ/-/kɪ/ gradient presented in opposing word-nonword contexts (GIFT-kift vs. giss-KISS), designed to bias perception toward lexical items. Phonetic perception shifted toward the direction of words, establishing a robust Ganong effect behaviorally. ERPs revealed a neural analog of lexical biasing emerging within ~200 msec. Source analyses uncovered a distributed neural network supporting the Ganong including middle temporal gyrus, inferior parietal lobe, and middle frontal cortex. Yet, among Ganong-sensitive regions, only left middle temporal gyrus and inferior parietal lobe predicted behavioral susceptibility to lexical influence. Our findings confirm lexical status rapidly constrains sublexical categorical representations for speech within several hundred milliseconds but likely does so outside the purview of canonical auditory-sensory brain areas.

Dynamic EEG analysis during language comprehension reveals interactive cascades between perceptual processing and sentential expectations

Understanding spoken language requires analysis of the rapidly unfolding speech signal at multiple levels: acoustic, phonological, and semantic. However, there is not yet a comprehensive picture of how these levels relate. We recorded electroencephalography (EEG) while listeners (N = 31) heard sentences in which we manipulated acoustic ambiguity (e.g., a bees/peas continuum) and sentential expectations (e.g., Honey is made by bees). EEG was analyzed with a mixed effects model over time to quantify how language processing cascades proceed on a millisecond-by-millisecond basis. Our results indicate: (1) perceptual processing and memory for fine-grained acoustics is preserved in brain activity for up to 900 msec; (2) contextual analysis begins early and is graded with respect to the acoustic signal; and (3) top-down predictions influence perceptual processing in some cases, however, these predictions are available simultaneously with the veridical signal. These mechanistic insights provide a basis for a better understanding of the cortical language network.

Relational Morphology: A Cousin of Construction Grammar

Relational morphology (RM) is a novel approach to word structure that bears a close relation to construction grammar (CxG). Based on the parallel architecture framework, its basic question is: what linguistic entities are stored in long-term memory, and in what form? Like CxG, RM situates the “rules of grammar” in an extended lexicon, right along with words, multiword expressions such as idioms and collocations, and meaningful syntactic constructions. However, its notion of schema enriches CxG’s notion of construction in a number of respects, including (a) the possibility of purely formal schemas that lack meaning, (b) a more precise way of specifying relations among lexical items than standard inheritance, (c) the possibility of “horizontal” relations between individual words and between schemas, (d) a clearer characterization of the distinction between productive and nonproductive phenomena, and (e) more explicit integration with theories of language processing and of other domains of cognition.

Transformation of a temporal speech cue to a spatial neural code in human auditory cortex

In speech, listeners extract continuously-varying spectrotemporal cues from the acoustic signal to perceive discrete phonetic categories. Spectral cues are spatially encoded in the amplitude of responses in phonetically-tuned neural populations in auditory cortex. It remains unknown whether similar neurophysiological mechanisms encode temporal cues like voice-onset time (VOT), which distinguishes sounds like /b/ and/p/. We used direct brain recordings in humans to investigate the neural encoding of temporal speech cues with a VOT continuum from /ba/ to /pa/. We found that distinct neural populations respond preferentially to VOTs from one phonetic category, and are also sensitive to sub-phonetic VOT differences within a population's preferred category. In a simple neural network model, simulated populations tuned to detect either temporal gaps or coincidences between spectral cues captured encoding patterns observed in real neural data. These results demonstrate that a spatial/amplitude neural code underlies the cortical representation of both spectral and temporal speech cues.

The time-course of speech perception revealed by temporally-sensitive neural measures

Recent advances in cognitive neuroscience have provided a detailed picture of the early time-course of speech perception. In this review, we highlight this work, placing it within the broader context of research on the neurobiology of speech processing, and discuss how these data point us toward new models of speech perception and spoken language comprehension. We focus, in particular, on temporally-sensitive measures that allow us to directly measure early perceptual processes. Overall, the data provide support for two key principles: (a) speech perception is based on gradient representations of speech sounds and (b) speech perception is interactive and receives input from higher-level linguistic context at the earliest stages of cortical processing. Implications for models of speech processing and the neurobiology of language more broadly are discussed. This article is categorized under: Psychology > Language Psychology > Perception and Psychophysics Neuroscience > Cognition.

Shaping perceptual learning of synthetic speech through feedback

Listeners exposed to accented speech must adjust how they map between acoustic features and lexical representations such as phonetic categories. A robust form of this adaptive perceptual learning is learning to perceive synthetic speech where the connections between acoustic features and phonetic categories must be updated. Both implicit learning through mere exposure and explicit learning through directed feedback have previously been shown to produce this type of adaptive learning. The present study crosses implicit exposure and explicit feedback with the presence or absence of a written identification task. We show that simple exposure produces some learning, but explicit feedback produces substantially stronger learning, whereas requiring written identification did not measurably affect learning. These results suggest that explicit feedback guides learning of new mappings between acoustic patterns and known phonetic categories. We discuss mechanisms that may support learning via implicit exposure.

Universals of listening: Equivalent prosodic entrainment in tone and non-tone languages

In English and Dutch, listeners entrain to prosodic contours to predict where focus will fall in an utterance. Here, we ask whether this strategy is universally available, even in languages with very different phonological systems (e.g., tone versus non-tone languages). In a phoneme detection experiment, we examined whether prosodic entrainment also occurs in Mandarin Chinese, a tone language, where the use of various suprasegmental cues to lexical identity may take precedence over their use in salience. Consistent with the results from Germanic languages, response times were facilitated when preceding intonation predicted high stress on the target-bearing word, and the lexical tone of the target word (i.e., rising versus falling) did not affect the Mandarin listeners' response. Further, the extent to which prosodic entrainment was used to detect the target phoneme was the same in both English and Mandarin listeners. Nevertheless, native Mandarin speakers did not adopt an entrainment strategy when the sentences were presented in English, consistent with the suggestion that L2 listening may be strained by additional functional load from prosodic processing. These findings have implications for how universal and language-specific mechanisms interact in the perception of focus structure in everyday discourse.

Diferencias temporales y espaciales en el procesamiento de incongruencias léxicas: un estudio de potenciales relacionados a eventos

Introducción. La comprensión del lenguaje está determinada por diversos procesos, entre los que se encuentra el reconocimiento léxico. Según el modelo conexionista, este reconocimiento se genera por activación mediante el emparejamiento de la información acumulada y por la inhibición de las entradas léxicas que compiten por activación.Objetivo. Determinar las diferencias temporales y espaciales de procesamiento entre las incongruencias léxicas semánticamente relacionadas a un contexto lingüístico oracional y las no relacionadas.Materiales y métodos. Se realizó medición de los potenciales relacionados a eventos en 10 sujetos sanos por medio de un paradigma de 240 oraciones en español agrupadas de la siguiente manera: 80 oraciones congruentes, 80 con incongruencias dentro del campo léxico y 80 con incongruencias fuera del campo léxico.Resultados. Se observó una diferencia estadística en la latencia de aparición del componente N400 entre las dos condiciones. Por su parte, se encontró una mayor activación del precúneo, del giro orbitofrontal, del giro angular y del giro supramarginal en la condición de incongruencia fuera del campo léxico.Conclusión. Se encontraron diferencias temporales y espaciales (activación del precúneo, del giro orbitofrontal, del giro angular y del giro supramarginal) entre el procesamiento de las incongruencias léxicas y no léxicas.

Ganong effects for frequency may not be robust

The Ganong effect-more identifications of a certain phoneme in a context where that phoneme would yield a real word than a context where that phoneme would yield a pseudoword-has been widely replicated. Few studies, however, have tested whether this effect occurs for frequency contrasts. In the present study, participants' likelihood of identifying an ambiguous sound as aspirated was tested in acoustically identical continua in contexts where the identification of the sound as aspirated would either yield a lower- or higher-frequency word than the identification of the sound as unaspirated would. No frequency-based Ganong effect was found.

Written sentence context effects on acoustic-phonetic perception: fMRI reveals cross-modal semantic-perceptual interactions

This study examines cross-modality effects of a semantically-biased written sentence context on the perception of an acoustically-ambiguous word target identifying neural areas sensitive to interactions between sentential bias and phonetic ambiguity. Of interest is whether the locus or nature of the interactions resembles those previously demonstrated for auditory-only effects. FMRI results show significant interaction effects in right mid-middle temporal gyrus (RmMTG) and bilateral anterior superior temporal gyri (aSTG), regions along the ventral language comprehension stream that map sound onto meaning. These regions are more anterior than those previously identified for auditory-only effects; however, the same cross-over interaction pattern emerged implying similar underlying computations at play. The findings suggest that the mechanisms that integrate information across modality and across sentence and phonetic levels of processing recruit amodal areas where reading and spoken lexical and semantic access converge. Taken together, results support interactive accounts of speech and language processing.

Neural Signal to Violations of Abstract Rules Using Speech-Like Stimuli

As the evidence of predictive processes playing a role in a wide variety of cognitive domains increases, the brain as a predictive machine becomes a central idea in neuroscience. In auditory processing, a considerable amount of progress has been made using variations of the Oddball design, but most of the existing work seems restricted to predictions based on physical features or conditional rules linking successive stimuli. To characterize the predictive capacity of the brain to abstract rules, we present here two experiments that use speech-like stimuli to overcome limitations and avoid common confounds. Pseudowords were presented in isolation, intermixed with infrequent deviants that contained unexpected phoneme sequences. As hypothesized, the occurrence of unexpected sequences of phonemes reliably elicited an early prediction error signal. These prediction error signals do not seemed to be modulated by attentional manipulations due to different task instructions, suggesting that the predictions are deployed even when the task at hand does not volitionally involve error detection. In contrast, the amount of syllables congruent with a standard pseudoword presented before the point of deviance exerted a strong modulation. Prediction error's amplitude doubled when two congruent syllables were presented instead of one, despite keeping local transitional probabilities constant. This suggests that auditory predictions can be built integrating information beyond the immediate past. In sum, the results presented here further contribute to the understanding of the predictive capabilities of the human auditory system when facing complex stimuli and abstract rules.

Semantic Context Enhances the Early Auditory Encoding of Natural Speech

Speech perception involves the integration of sensory input with expectations based on the context of that speech. Much debate surrounds the issue of whether or not prior knowledge feeds back to affect early auditory encoding in the lower levels of the speech processing hierarchy, or whether perception can be best explained as a purely feedforward process. Although there has been compelling evidence on both sides of this debate, experiments involving naturalistic speech stimuli to address these questions have been lacking. Here, we use a recently introduced method for quantifying the semantic context of speech and relate it to a commonly used method for indexing low-level auditory encoding of speech. The relationship between these measures is taken to be an indication of how semantic context leading up to a word influences how its low-level acoustic and phonetic features are processed. We record EEG from human participants (both male and female) listening to continuous natural speech and find that the early cortical tracking of a word's speech envelope is enhanced by its semantic similarity to its sentential context. Using a forward modeling approach, we find that prediction accuracy of the EEG signal also shows the same effect. Furthermore, this effect shows distinct temporal patterns of correlation depending on the type of speech input representation (acoustic or phonological) used for the model, implicating a top-down propagation of information through the processing hierarchy. These results suggest a mechanism that links top-down prior information with the early cortical entrainment of words in natural, continuous speech.SIGNIFICANCE STATEMENT During natural speech comprehension, we use semantic context when processing information about new incoming words. However, precisely how the neural processing of bottom-up sensory information is affected by top-down context-based predictions remains controversial. We address this discussion using a novel approach that indexes a word's similarity to context and how well a word's acoustic and phonetic features are processed by the brain at the time of its utterance. We relate these two measures and show that lower-level auditory tracking of speech improves for words that are more related to their preceding context. These results suggest a mechanism that links top-down prior information with bottom-up sensory processing in the context of natural, narrative speech listening.