Publications

Abstract

This psychoacoustic study provides behavioral evidence that neural entrainment in the theta range (3-9 Hz) causally shapes speech perception. Adopting the ‘rate normalization’ paradigm (presenting compressed carrier sentences followed by uncompressed target words), we show that uniform compression of a speech carrier to syllable rates inside the theta range influences perception of subsequent uncompressed targets, but compression outside theta range does not. However, the influence of carriers – compressed outside theta range – on target perception is salvaged when carriers are ‘repackaged’ to have a packet rate inside theta. This suggests that the brain can only successfully entrain to syllable/packet rates within theta range, with a causal influence on the perception of subsequent speech, in line with recent neuroimaging data. Thus, this study points to a central role for sustained theta entrainment in rate normalization and contributes to our understanding of the functional role of brain oscillations in speech perception.

Abstract

Recently, the world’s attention was caught by an audio clip that was perceived as “Laurel” or “Yanny”. Opinions were sharply split: many could not believe others heard something different from their perception. However, a crowd-source experiment with >500 participants shows that it is possible to make people hear Laurel, where they previously heard Yanny, by manipulating preceding acoustic context. This study is not only the first to reveal within-listener variation in Laurel/Yanny percepts, but also to demonstrate contrast effects for global spectral information in larger frequency regions. Thus, it highlights the intricacies of human perception underlying these social media phenomena.

Abstract

Speakers adjust their voice when talking in noise (known as Lombard speech), facilitating speech comprehension. Recent neurobiological models of speech perception emphasize the role of amplitude modulations in speech-in-noise comprehension, helping neural oscillators to ‘track’ the attended speech. This study tested whether talkers produce more pronounced amplitude modulations in noise. Across four different corpora, modulation spectra showed greater power in amplitude modulations below 4 Hz in Lombard speech compared to matching plain speech. This suggests that noise-induced speech contains more pronounced amplitude modulations, potentially helping the listening brain to entrain to the attended talker, aiding comprehension.

Abstract

Learning a language involves learning how to map specific forms onto their associated meanings. Such mappings can utilise arbitrariness and non-arbitrariness, yet, our understanding of how these two systems operate at different stages of vocabulary development is still not fully understood. The Sound-Symbolism Bootstrapping Hypothesis (SSBH) proposes that sound-symbolism is essential for word learning to commence, but empirical evidence of exactly how sound-symbolism influences language learning is still sparse. It may be the case that sound-symbolism supports acquisition of categories of meaning, or that it enables acquisition of individualized word meanings. In two Experiments where participants learned form-meaning mappings from either sound-symbolic or arbitrary languages, we demonstrate the changing roles of sound-symbolism and arbitrariness for different vocabulary sizes, showing that sound-symbolism provides an advantage for learning of broad categories, which may then transfer to support learning individual words, whereas an arbitrary language impedes acquisition of categories of sound to meaning.

Abstract

This chapter focuses on connectionist modeling in language production, highlighting how
core principles of connectionism provide coverage for empirical observations about
representation and selection at the phonological, lexical, and sentence levels. The first
section focuses on the connectionist principles of localist representations and spreading
activation. It discusses how these two principles have motivated classic models of speech
production and shows how they cover results of the picture-word interference paradigm,
the mixed error effect, and aphasic naming errors. The second section focuses on how
newer connectionist models incorporate the principles of learning and distributed
representations through discussion of syntactic priming, cumulative semantic
interference, sequencing errors, phonological blends, and code-switching

Abstract

Individual alpha frequency (IAF) is a promising electrophysiological marker of interindividual differences in cognitive function. IAF has been linked with trait-like differences in information processing and general intelligence, and provides an empirical basis for the definition of individualized frequency bands. Despite its widespread application, however, there is little consensus on the optimal method for estimating IAF, and many common approaches are prone to bias and inconsistency. Here, we describe an automated strategy for deriving two of the most prevalent IAF estimators in the literature: peak alpha frequency (PAF) and center of gravity (CoG). These indices are calculated from resting-state power spectra that have been smoothed using a Savitzky-Golay filter (SGF). We evaluate the performance characteristics of this analysis procedure in both empirical and simulated EEG data sets. Applying the SGF technique to resting-state data from n = 63 healthy adults furnished 61 PAF and 62 CoG estimates. The statistical properties of these estimates were consistent with previous reports. Simulation analyses revealed that the SGF routine was able to reliably extract target alpha components, even under relatively noisy spectral conditions. The routine consistently outperformed a simpler method of automated peak detection that did not involve spectral smoothing. The SGF technique is fast, open source, and available in two popular programming languages (MATLAB, Python), and thus can easily be integrated within the most popular M/EEG toolsets (EEGLAB, FieldTrip, MNE-Python). As such, it affords a convenient tool for improving the reliability and replicability of future IAF-related research.

Abstract

How a system represents information tightly constrains the kinds of problems it can solve. Humans routinely solve problems that appear to require structured representations of stimulus properties and the relations between them. An account of how we might acquire such representations has central importance for theories of human cognition. We describe how a system can learn structured relational representations from initially unstructured inputs using comparison, sensitivity to time, and a modified Hebbian learning algorithm. We summarize how the model DORA (Discovery of Relations by Analogy) instantiates this approach, which we call predicate learning, as well as how the model captures several phenomena from cognitive development, relational reasoning, and language processing in the human brain. Predicate learning offers a link between models based on formal languages and models which learn from experience and provides an existence proof for how structured representations might be learned in the first place.

Abstract

Numerous studies in psychology, cognitive neuroscience and psycholinguistics have used pictures of objects as stimulus materials. Currently, authors engaged in cross-linguistic work or wishing to run parallel studies at multiple sites where different languages are spoken must rely on rather small sets of black-and-white or colored line drawings. These sets are increasingly experienced as being too limited. Therefore, we constructed a new set of 750 colored pictures of concrete concepts. This set, MultiPic, constitutes a new valuable tool for cognitive scientists investigating language, visual perception, memory and/or attention in monolingual or multilingual populations. Importantly, the MultiPic databank has been normed in six different European languages (British English, Spanish, French, Dutch, Italian and German). All stimuli and norms are freely available at http://www.bcbl.eu/databases/multipic

Abstract

In contrast to the large amount of dual-task research investigating the coordination of a linguistic and a nonlinguistic
task, little research has investigated how two linguistic tasks are coordinated. However, such research
would greatly contribute to our understanding of how interlocutors combine speech planning and listening in
conversation. In three dual-task experiments we studied how participants coordinated the processing of an
auditory stimulus (S1), which was either a syllable or a tone, with selecting a name for a picture (S2). Two SOAs,
of 0 ms and 1000 ms, were used. To vary the time required for lexical selection and to determine when lexical
selection took place, the pictures were presented with categorically related or unrelated distractor words. In
Experiment 1 participants responded overtly to both stimuli. In Experiments 2 and 3, S1 was not responded to
overtly, but determined how to respond to S2, by naming the picture or reading the distractor aloud. Experiment
1 yielded additive effects of SOA and distractor type on the picture naming latencies. The presence of semantic
interference at both SOAs indicated that lexical selection occurred after response selection for S1. With respect to
the coordination of S1 and S2 processing, Experiments 2 and 3 yielded inconclusive results. In all experiments,
syllables interfered more with picture naming than tones. This is likely because the syllables activated phonological
representations also implicated in picture naming. The theoretical and methodological implications of the
findings are discussed.

Abstract

Resource-constrained models of language processing predict that perceptual simulation during language understanding would be compromised by sensory limitations (such as reading text in unfamiliar/difficult font), whereas strong versions of embodied theories of language would predict that simulating perceptual symbols in language would not be impaired even under sensory-constrained situations. In 2 experiments, sensory decoding difficulty was manipulated by using easy and hard fonts to study perceptual simulation during sentence reading (Zwaan, Stanfield, & Yaxley, 2002). Results indicated that simulating perceptual symbols in language was not compromised by surface-form decoding challenges such as difficult font, suggesting relative resilience of embodied language processing in the face of certain sensory constraints. Further implications for learning from text and individual differences in language processing will be discussed

Abstract

Literacy affects many aspects of cognitive and linguistic processing. Among them, it increases the salience of words as units of linguistic processing. Here, we explored the impact of literacy acquisition on children’s learning of an artifical language. Recent accounts of L1–L2 differences relate adults’ greater difficulty with language learning to their smaller reliance on multiword units. In particular, multiword units are claimed to be beneficial for learning opaque grammatical relations like grammatical gender. Since literacy impacts the reliance on words as units of processing, we ask if and how acquiring literacy may change children’s language-learning results. We looked at children’s success in learning novel noun labels relative to their success in learning article-noun gender agreement, before and after learning to read. We found that preliterate first graders were better at learning agreement (larger units) than at learning nouns (smaller units), and that the difference between the two trial types significantly decreased after these children acquired literacy. In contrast, literate third graders were as good in both trial types. These findings suggest that literacy affects not only language processing, but also leads to important differences in language learning. They support the idea that some of children’s advantage in language learning comes from their previous knowledge and experience with language—and specifically, their lack of experience with written texts.

Abstract

Introduction to the special issue 'The Effects of Literacy on Cognition and Brain Functioning'

Abstract

The cause of developmental dyslexia is still unknown despite decades of intense research. Many causal explanations have been proposed, based on the range of impairments displayed by affected individuals. Here we draw attention to the fact that many of these impairments are also shown by illiterate individuals who have not received any or very little reading instruction. We suggest that this fact may not be coincidental and that the performance differences of both illiterates and individuals with dyslexia compared to literate controls are, to a substantial extent, secondary consequences of either reduced or suboptimal reading experience or a combination of both. The search for the primary causes of reading impairments will make progress if the consequences of quantitative and qualitative differences in reading experience are better taken into account and not mistaken for the causes of reading disorders. We close by providing four recommendations for future research.

Abstract

This study uses a sentence completion task with Swedish and Chinese L2 English speakers to investigate how L1 morphosyntax and L2 proficiency influence L2 English subject-verb agreement production. Chinese has limited nominal and verbal number morphology, while Swedish has robust noun phrase (NP) morphology but does not number-mark verbs. Results showed that like L1 English speakers, both L2 groups used grammatical and conceptual number to produce subject-verb agreement. However, only L1 Chinese speakers—and less-proficient speakers in both L2 groups—were similarly influenced by grammatical and conceptual number when producing the subject NP. These findings demonstrate how L2 proficiency, perhaps combined with cross-linguistic differences, influence L2 production and underscore that encoding of noun and verb number are not independent.

Abstract

Zwaan et al. mention that young researchers should conduct replications as a
small part of their portfolio. We extend this proposal and suggest that conducting and
reporting replications should become an integral part of PhD projects and be taken into
account in their assessment. We discuss how this would help not only scientific
advancement, but also PhD candidates’ careers.

Abstract

The leading theories of sentence planning – Hierarchical Incrementality and Linear Incrementality – differ in their assumptions about the coordination of processes that map preverbal information onto language. Previous studies showed that, in native (L1) speakers, this coordination can vary with the ease of executing the message-level and sentence-level processes necessary to plan and produce an utterance. We report the first series of experiments to systematically examine how linguistic experience influences sentence planning in native (L1) speakers (i.e., speakers with life-long experience using the target language) and non-native (L2) speakers (i.e., speakers with less experience using the target language). In all experiments, speakers spontaneously generated one-sentence descriptions of simple events in Dutch (L1) and English (L2). Analyses of eye-movements across early and late time windows (pre- and post-400 ms) compared the extent of early message-level encoding and the onset of linguistic encoding. In Experiment 1, speakers were more likely to engage in extensive message-level encoding and to delay sentence-level encoding when using their L2. Experiments 2–4 selectively facilitated encoding of the preverbal message, encoding of the agent character (i.e., the first content word in active sentences), and encoding of the sentence verb (i.e., the second content word in active sentences) respectively. Experiment 2 showed that there is no delay in the onset of L2 linguistic encoding when speakers are familiar with the events. Experiments 3 and 4 showed that the delay in the onset of L2 linguistic encoding is not due to speakers delaying encoding of the agent, but due to a preference to encode information needed to select a suitable verb early in the formulation process. Overall, speakers prefer to temporally separate message-level from sentence-level encoding and to prioritize encoding of relational information when planning L2 sentences, consistent with Hierarchical Incrementality

Abstract

Low-frequency neural entrainment to rhythmic input
has been hypothesized as a canonical mechanism
that shapes sensory perception in time. Neural
entrainment is deemed particularly relevant for
speech analysis, as it would contribute to the extraction
of discrete linguistic elements from continuous
acoustic signals. However, its causal influence in
speech perception has been difficult to establish.
Here, we provide evidence that oscillations build temporal
predictions about the duration of speech tokens
that affect perception. Using magnetoencephalography
(MEG), we studied neural dynamics during
listening to sentences that changed in speech rate.
Weobserved neural entrainment to preceding speech
rhythms persisting for several cycles after the change
in rate. The sustained entrainment was associated
with changes in the perceived duration of the last
word’s vowel, resulting in the perception of words
with different meanings. These findings support oscillatory
models of speech processing, suggesting that
neural oscillations actively shape speech perception.

Abstract

In response to recommendations to redefine statistical significance to P ≤ 0.005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level.

Abstract

We learn language from our social environment, but the more sources we have, the less informative each source is, and therefore, the less weight we ascribe its input. According to this principle, people with larger social networks should give less weight to new incoming information, and should therefore be less susceptible to the influence of new speakers. This paper tests this prediction, and shows that speakers with smaller social networks indeed have more malleable linguistic representations. In particular, they are more likely to adjust their lexical boundary following exposure to a new speaker. Experiment 2 uses computational simulations to test whether this greater malleability could lead people with smaller social networks to be important for the propagation of linguistic change despite the fact that they interact with fewer people. The results indicate that when innovators were connected with people with smaller rather than larger social networks, the population exhibited greater and faster diffusion. Together these experiments show that the properties of people’s social networks can influence individuals’ learning and use as well as linguistic phenomena at the community level.

Abstract

Infants and adults learn new phonological varieties better when exposed to multiple rather than a single speaker. This
article tests whether having a larger social network similarly facilitates phonological performance. Experiment 1 shows
that people with larger social networks are better at vowel perception in noise, indicating that the benefit of laboratory
exposure to multiple speakers extends to real life experience and to adults tested in their native language. Furthermore,
the experiment shows that this association is not due to differences in amount of input or to cognitive differences
between people with different social network sizes. Follow-up computational simulations reveal that the benefit of
larger social networks is mostly due to increased input variability. Additionally, the simulations show that the boost
that larger social networks provide is independent of the amount of input received but is larger if the population is
more heterogeneous. Finally, a comparison of “adult” and “child” simulations reconciles previous conflicting findings
by suggesting that input variability along the relevant dimension might be less useful at the earliest stages of learning.
Together, this article shows when and how the size of our social network influences our speech perception. It thus
shows how aspects of our lifestyle can influence our linguistic performance.

Abstract

Language processing requires us to integrate incoming linguistic representations with representations of past input, often across intervening words and phrases. This computational situation has been argued to require retrieval of the appropriate representations from memory via a set of features or representations serving as retrieval cues. However, even within in a cue-based retrieval account of language comprehension, both the structure of retrieval cues and the particular computation that underlies direct-access retrieval are still underspecified. Evidence from two event-related brain potential (ERP) experiments that show cue-based interference from different types of linguistic representations during ellipsis comprehension are consistent with an architecture wherein different cue types are integrated, and where the interaction of cue with the recent contents of memory determines processing outcome, including expression of the interference effect in ERP componentry. I conclude that retrieval likely includes a computation where cues are integrated with the contents of memory via a linear weighting scheme, and I propose vector addition as a candidate formalization of this computation. I attempt to account for these effects and other related phenomena within a broader cue-based framework of language processing.

Abstract

Language comprehension involves coping with ambiguity and recovering from misanalysis. Syntactic ambiguity resolution is associated with increased reading times, a classic finding that has shaped theories of sentence processing. However, reaction times conflate the time it takes a process to complete with the quality of the behavior-related information available to the system. We therefore used the speed-accuracy tradeoff procedure (SAT) to derive orthogonal estimates of processing time and interpretation accuracy, and tested whether stronger retrieval cues (via semantic relatedness: neighed->horse vs. fell->horse) aid interpretation during recovery. On average, ambiguous sentences took 250ms longer (SAT rate) to interpret than unambiguous controls, demonstrating veridical differences in processing time. Retrieval cues more strongly related to the true subject always increased accuracy, regardless of ambiguity. These findings are consistent with a language processing architecture where cue-driven operations give rise to interpretation, and wherein diagnostic cues aid retrieval, regardless of parsing difficulty or structural uncertainty.

Abstract

Listeners are known to use adjacent contextual speech rate in processing temporally ambiguous speech sounds. For instance, an ambiguous vowel between short /A/ and long /a:/ in Dutch sounds relatively long (i.e., as /a:/) embedded in a fast precursor sentence, but short in a slow sentence. Besides the local speech rate, listeners also track talker-specific global speech rates. However, it is yet unclear whether other talkers' global rates are encoded with reference to a listener's self-produced rate. Three experiments addressed this question. In Experiment 1, one group of participants was instructed to speak fast, whereas another group had to speak slowly. The groups were compared on their perception of ambiguous /A/-/a:/ vowels embedded in neutral rate speech from another talker. In Experiment 2, the same participants listened to playback of their own speech and again evaluated target vowels in neutral rate speech. Neither of these experiments provided support for the involvement of self-produced speech in perception of another talker's speech rate. Experiment 3 repeated Experiment 2 but with a new participant sample that was unfamiliar with the participants from Experiment 2. This experiment revealed fewer /a:/ responses in neutral speech in the group also listening to a fast rate, suggesting that neutral speech sounds slow in the presence of a fast talker and vice versa. Taken together, the findings show that self-produced speech is processed differently from speech produced by others. They carry implications for our understanding of the perceptual and cognitive mechanisms involved in rate-dependent speech perception in dialogue settings.

Abstract

As conversation is the most important way of using language, linguists and psychologists should combine forces to investigate how interlocutors deal with the cognitive demands arising during conversation. Linguistic analyses of corpora of conversation are needed to understand the structure of conversations, and experimental work is indispensable for understanding the underlying cognitive processes. We argue that joint consideration of corpus and experimental data is most informative when the utterances elicited in a lab experiment match those extracted from a corpus in relevant ways. This requirement to compare like with like seems obvious but is not trivial to achieve. To illustrate this approach, we report two experiments where responses to polar (yes/no) questions were elicited in the lab and the response latencies were compared to gaps between polar questions and answers in a corpus of conversational speech. We found, as expected, that responses were given faster when they were easy to plan and planning could be initiated earlier than when they were harder to plan and planning was initiated later. Overall, in all but one condition, the latencies were longer than one would expect based on the analyses of corpus data. We discuss the implication of this partial match between the data sets and more generally how corpus and experimental data can best be combined in studies of conversation.

Abstract

Propagation of novel linguistic terms is an important aspect of language use and language
change. Here, we test how social network size influences people’s likelihood of adopting novel
labels by examining hashtag use on Twitter. Specifically, we test whether following fewer Twitter
users leads to more varied and malleable hashtag use on Twitter , because each followed user is
ascribed greater weight and thus exerts greater influence on the following user. Focusing on Dutch
users tweeting about the terrorist attack in Brussels in 2016, we show that people who follow
fewer other users use a larger number of unique hashtags to refer to the event, reflecting greater
malleability and variability in use. These results have implications for theories of language learning, language use, and language change.

Abstract

Do people routinely pre-activate the meaning and even the phonological form of upcoming words? The most acclaimed evidence for phonological prediction comes from a 2005 Nature Neuroscience publication by DeLong, Urbach and Kutas, who observed a graded modulation of electrical brain potentials (N400) to nouns and preceding articles by the probability that people use a word to continue the sentence fragment (‘cloze’). In our direct replication study spanning 9 laboratories (N=334), pre-registered replication-analyses and exploratory Bayes factor analyses successfully replicated the noun-results but, crucially, not the article-results. Pre-registered single-trial analyses also yielded a statistically significant effect for the nouns but not the articles. Exploratory Bayesian single-trial analyses showed that the article-effect may be non-zero but is likely far smaller than originally reported and too small to observe without very large sample sizes. Our results do not support the view that readers routinely pre-activate the phonological form of predictable words.

Abstract

Implicit up/down words, such as bird and foot, systematically influence performance on visual tasks involving immediately following targets in compatible vs. incompatible locations. Recent studies have observed that the semantic relation between prime words and target pictures can strongly influence the size and even the direction of the effect: Semantically related targets are processed faster in congruent vs. incongruent locations (location-specific priming), whereas unrelated targets are processed slower in congruent locations. Here, we used eye-tracking to investigate the moment-to-moment processes underlying this pattern. Our reaction time results for related targets replicated the location-specific priming effect and showed a trend towards interference for unrelated targets. We then used growth curve analysis to test how up/down words and their match vs. mismatch with immediately following targets in terms of semantics and vertical location influences concurrent saccadic eye movements. There was a strong main effect of spatial association on linear growth with up words biasing changes in y-coordinates over time upwards relative to down words (and vice versa). Similar to the RT data, this effect was strongest for semantically related targets and reversed for unrelated targets. Intriguingly, all conditions showed a bias in the congruent direction in the initial stage of the saccade. Then, at around halfway into the saccade the effect kept increasing in the semantically related condition, and reversed in the unrelated condition. These results suggest that online processing of up/down words triggers direction-specific oculomotor processes that are dynamically modulated by the semantic relation between prime words and targets.

Abstract

A key challenge for cognitive neuroscience is deciphering the representational schemes of the brain. Stimulus-feature-based encoding models are becoming increasingly popular for inferring the dimensions of neural representational spaces from stimulus-feature spaces. We argue that such inferences are not always valid because successful prediction can occur even if the two representational spaces use different, but correlated, representational schemes. We support this claim with three simulations in which we achieved high prediction accuracy despite systematic differences in the geometries and dimensions of the underlying representations. Detailed analysis of the encoding models' predictions showed systematic deviations from ground-truth, indicating that high prediction accuracy is insufficient for making representational inferences. This fallacy applies to the prediction of actual neural patterns from stimulus-feature spaces and we urge caution in inferring the nature of the neural code from such methods. We discuss ways to overcome these inferential limitations, including model comparison, absolute model performance, visualization techniques and attentional modulation.

Abstract

Recent work suggests that cultural transmission can lead to the emergence of linguistic structure as speakers’ weak individual biases become amplified through iterated learning. However, to date no published study has demonstrated a similar emergence of linguistic structure in children. The lack of evidence from child learners constitutes a problematic
2
gap in the literature: if such learning biases impact the emergence of linguistic structure, they should also be found in children, who are the primary learners in real-life language transmission. However, children may differ from adults in their biases given age-related differences in general cognitive skills. Moreover, adults’ performance on iterated learning tasks may reflect existing (and explicit) linguistic biases, partially undermining the generality of the results. Examining children’s performance can also help evaluate contrasting predictions about their role in emerging languages: do children play a larger or smaller role than adults in the creation of structure? Here, we report a series of four iterated artificial language learning studies (based on Kirby, Cornish & Smith, 2008) with both children and adults, using a novel child-friendly paradigm. Our results show that linguistic structure does not emerge more readily in children compared to adults, and that adults are overall better in both language learning and in creating linguistic structure. When languages could become underspecified (by allowing homonyms), children and adults were similar in developing consistent mappings between meanings and signals in the form of structured ambiguities. However, when homonimity was not allowed, only adults created compositional structure. This study is a first step in using iterated language learning paradigms to explore child-adult differences. It provides the first demonstration that cultural transmission has a different effect on the languages produced by children and adults: While children were able to develop systematicity, their languages did not show compositionality. We focus on the relation between learning and structure creation as a possible explanation for our findings and discuss implications for children’s role in the emergence of linguistic structure.

Abstract

Infants, children and adults are capable of extracting recurring patterns from their environment through statistical learning (SL), an implicit learning mechanism that is considered to have an important role in language acquisition. Research over the past 20 years has shown that SL is present from very early infancy and found in a variety of tasks and across modalities (e.g., auditory, visual), raising questions on the domain generality of SL. However, while SL is well established for infants and adults, only little is known about its developmental trajectory during childhood, leaving two important questions unanswered: (1) Is SL an early-maturing capacity that is fully developed in infancy, or does it improve with age like other cognitive capacities (e.g., memory)? and (2) Will SL have similar developmental trajectories across modalities? Only few studies have looked at SL across development, with conflicting results: some find age-related improvements while others do not. Importantly, no study to date has examined auditory SL across childhood, nor compared it to visual SL to see if there are modality-based differences in the developmental trajectory of SL abilities. We addressed these issues by conducting a large-scale study of children's performance on matching auditory and visual SL tasks across a wide age range (5–12y). Results show modality-based differences in the development of SL abilities: while children's learning in the visual domain improved with age, learning in the auditory domain did not change in the tested age range. We examine these findings in light of previous studies and discuss their implications for modality-based differences in SL and for the role of auditory SL in language acquisition. A video abstract of this article can be viewed at: https://www.youtube.com/watch?v=3kg35hoF0pw.

Abstract

In language production research, the latency with which speakers produce a spoken response to a stimulus and the onset and offset times of words in longer utterances are key dependent variables. Measuring these variables automatically often yields partially incorrect results. However, exact measurements through the visual inspection of the recordings are extremely time-consuming. We present AlignTool, an open-source alignment tool that establishes preliminarily the onset and offset times of words and phonemes in spoken utterances using Praat, and subsequently performs a forced alignment of the spoken utterances and their orthographic transcriptions in the automatic speech recognition system MAUS. AlignTool creates a Praat TextGrid file for inspection and manual correction by the user, if necessary. We evaluated AlignTool’s performance with recordings of single-word and four-word utterances as well as semi-spontaneous speech. AlignTool performs well with audio signals with an excellent signal-to-noise ratio, requiring virtually no corrections. For audio signals of lesser quality, AlignTool still is highly functional but its results may require more frequent manual corrections. We also found that audio recordings including long silent intervals tended to pose greater difficulties for AlignTool than recordings filled with speech, which AlignTool analyzed well overall. We expect that by semi-automatizing the temporal analysis of complex utterances, AlignTool will open new avenues in language production research.

Abstract

When we comprehend language, we often do this in rich settings in which we can use many cues to understand what someone is saying. However, it has traditionally been difficult to design experiments with rich three-dimensional contexts that resemble our everyday environments, while maintaining control over the linguistic and non-linguistic information that is available. Here we test the validity of combining electroencephalography (EEG) and Virtual Reality (VR) to overcome this problem. We recorded electrophysiological brain activity during language processing in a well-controlled three-dimensional virtual audiovisual environment. Participants were immersed in a virtual restaurant, while wearing EEG equipment. In the restaurant participants encountered virtual restaurant guests. Each guest was seated at a separate table with an object on it (e.g. a plate with salmon). The restaurant guest would then produce a sentence (e.g. “I just ordered this salmon.”). The noun in the spoken sentence could either match (“salmon”) or mismatch (“pasta”) with the object on the table, creating a situation in which the auditory information was either appropriate or inappropriate in the visual context. We observed a reliable N400 effect as a consequence of the mismatch. This finding validates the combined use of VR and EEG as a tool to study the neurophysiological mechanisms of everyday language comprehension in rich, ecologically valid settings.

Abstract

Interpersonal discourse particles (DPs), such as Dutch inderdaad (≈‘indeed’) and eigenlijk (≈‘actually’) are highly frequent in everyday conversational interaction. Despite extensive theoretical descriptions of their polyfunctionality, little is known about how they are used by language comprehenders. In two visual world eye-tracking experiments involving an online dialogue completion task, we asked to what extent inderdaad, confirming an inferred expectation, and eigenlijk, contrasting with an inferred expectation, influence real-time understanding of dialogues. Answers in the dialogues contained a DP or a control adverb, and a critical discourse referent was replaced by a beep; participants chose the most likely dialogue completion by clicking on one of four referents in a display. Results show that listeners make rapid and fine-grained situation-specific inferences about the use of DPs, modulating their expectations about how the dialogue will unfold. Findings further specify and constrain theories about the conversation-managing function and polyfunctionality of DPs.

Abstract

The present study investigated the interplay between selective inhibition (the ability to suppress specific competing responses) and nonselective inhibition (the ability to suppress any inappropriate response) during single word production. To this end, we combined two well-established research paradigms: the picture-word interference task and the stop-signal task. Selective inhibition was assessed by instructing participants to name target pictures (e.g., dog) in the presence of semantically related (e.g., cat) or unrelated (e.g., window) distractor words. Nonselective inhibition was tested by occasionally presenting a visual stop-signal, indicating that participants should withhold their verbal response. The stop-signal was presented early (250 ms) aimed at interrupting the lexical selection stage, and late (325 ms) to influence the word-encoding stage of the speech production process. We found longer naming latencies for pictures with semantically related distractors than with unrelated distractors (semantic interference effect). The results further showed that, at both delays, stopping latencies (i.e., stop-signal RTs) were prolonged for naming pictures with semantically related distractors compared to pictures with unrelated distractors. Taken together, our findings suggest that selective and nonselective inhibition, at least partly, share a common inhibitory mechanism during different stages of the speech production process.

Abstract

The blocked cyclic naming paradigm has been increasingly employed to investigate the mechanisms underlying spoken word production. Semantic homogeneity typically elicits longer naming latencies than heterogeneity; however, it is debated whether competitive lexical selection or incremental learning underlies this effect. The current study manipulated both semantic and phonological homogeneity and used behavioural and electrophysiological measurements to provide evidence that can distinguish between the two accounts. Results show that naming latencies are longer in semantically homogeneous blocks, but shorter in phonologically homogeneous blocks, relative to heterogeneity. The semantic factor significantly modulates electrophysiological waveforms from 200 ms and the phonological factor from 350 ms after picture presentation. A positive component was demonstrated in both manipulations, possibly reflecting a task-related top-down bias in performing blocked cyclic naming. These results provide novel insights into the neural correlates of blocked cyclic naming and further contribute to the understanding of spoken word production.