Publications

Abstract

The purpose of this study was to relate a psycholinguistic processing model of picture naming to the dynamics of cortical activation during picture naming. The activation was recorded from eight Dutch subjects with a whole-head neuromagnetometer. The processing model, based on extensive naming latency studies, is a stage model. In preparing a picture's name, the speaker performs a chain of specific operations. They are, in this order, computing the visual percept, activating an appropriate lexical concept, selecting the target word from the mental lexicon, phonological encoding, phonetic encoding, and initiation of articulation. The time windows for each of these operations are reasonably well known and could be related to the peak activity of dipole sources in the individual magnetic response patterns. The analyses showed a clear progression over these time windows from early occipital activation, via parietal and temporal to frontal activation. The major specific findings were that (1) a region in the left posterior temporal lobe, agreeing with the location of Wernicke's area, showed prominent activation starting about 200 msec after picture onset and peaking at about 350 msec, (i.e., within the stage of phonological encoding), and (2) a consistent activation was found in the right parietal cortex, peaking at about 230 msec after picture onset, thus preceding and partly overlapping with the left temporal response. An interpretation in terms of the management of visual attention is proposed.

Abstract

The evolution of speech and language has been a returning topic in the language sciences since the so-called “cognitive revolution.”

Abstract

Since the Enlightenment period, natural theories of speech and language evolution have florished in the language sciences. Four ever returning core issues are highlighted in this paper: Firstly, Is language natural to man or just an invention? Secondly, Is language a specific human ability (a ‘language instinct’) or does it arise from general cognitive capacities we share with other animals? Thirdly, Has the evolution of language been a gradual process or did it rather suddenly arise, due to some ‘evolutionary twist’? Lastly, Is the child's language acquisition an appropriate model for language evolution?

Abstract

This commentary discusses whether abstract metrical frames are stored. For stress-assigning languages (e.g., Dutch and English), which have a dominant stress pattern, metrical frames are stored only for words that deviate from the default stress pattern. The majority of the words in these languages are produced without retrieving any independent syllabic or metrical frame.

Abstract

This paper considers the AGL literature from a psycholinguistic perspective. It first presents a taxonomy of the experimental familiarization test procedures used, which is followed by a consideration of shortcomings and potential improvements of the empirical methodology. It then turns to reconsidering the issue of grammar learning from the point of view of acquiring constraints, instead of the traditional AGL approach in terms of acquiring sets of rewrite rules. This is, in particular, a natural way of handling long‐distance dependences. The final section addresses an underdeveloped issue in the AGL literature, namely how to detect latent hierarchical structure in AGL response patterns.

Abstract

In recent decades, psychologists have become increasingly interested in our ability to speak. This paper sketches the present theoretical perspective on this most complex skill of homo sapiens. The generation of fluent speech is based on the interaction of various processing components. These mechanisms are highly specialized, dedicated to performing specific subroutines, such as retrieving appropriate words, generating morpho-syntactic structure, computing the phonological target shape of syllables, words, phrases and whole utterances, and creating and executing articulatory programmes. As in any complex skill, there is a self-monitoring mechanism that checks the output. These component processes are targets of increasingly sophisticated experimental research, of which this paper presents a few salient examples.

Abstract

The present paper studies how, in deictic expressions, the temporal interdependency of speech and gesture is realized in the course of motor planning and execution. Two theoretical positions were compared. On the “interactive” view the temporal parameters of speech and gesture are claimed to be the result of feedback between the two systems throughout the phases of motor planning and execution. The alternative “ballistic” view, however, predicts that the two systems are independent during the phase of motor execution, the temporal parameters having been preestablished in the planning phase. In four experiments subjects were requested to indicate which of an array of referent lights was momentarily illuminated. This was done by pointing to the light and/or by using a deictic expression (this/that light). The temporal and spatial course of the pointing movement was automatically registered by means of a Selspot opto-electronic system. By analyzing the moments of gesture initiation and apex, and relating them to the moments of speech onset, it was possible to show that, for deictic expressions, the ballistic view is very nearly correct.

Abstract

The core issue in the 19-century sources of psycholinguistics was the question, "Where does language come from?'' This genetic perspective unified the study of the ontogenesis, the phylogenesis, the microgenesis, and to some extent the neurogenesis of language. This paper makes the point that this original perspective is still a valid and attractive one. It is exemplified by a discussion of the genesis of spoken words.

Abstract

It has been hypothesised that human reasoning has a non-linguistic foundation, but is nevertheless influenced by the formal means available in a language. For example, Western logic is transparently related to European sentential connectives (e.g., and, if … then, or, not), some of which cannot be unambiguously expressed in other languages. The questionnaire explores reasoning tools and practices through investigating translation equivalents of English sentential connectives and collecting examples of “reasoned arguments”.

Abstract

Demonstratives play a crucial role in the acquisition and use of language. Bringing together a team of leading scholars this detailed study, a first of its kind, explores meaning and use across fifteen typologically and geographically unrelated languages to find out what cross-linguistic comparisons and generalizations can be made, and how this might challenge current theory in linguistics, psychology, anthropology and philosophy. Using a shared experimental task, rounded out with studies of natural language use, specialists in each of the languages undertook extensive fieldwork for this comparative study of semantics and usage. An introduction summarizes the shared patterns and divergences in meaning and use that emerge.

Abstract

This paper confronts Kant’s (1768) view of human conceptions of space as fundamentally divided along the three planes of the human body with an empirical case study in the Mayan community of Tenejapa in southern Mexico, whose inhabitants do not use left/right distinctions to project regions in space. Tenejapans have names for the left hand and the right hand, and also a term for hand/arm in general, but they do not generalize the distinction to spatial regions -- there is no linguistic expression glossing as 'to the left' or 'on the left-hand side', for example. Tenejapans also show a remarkable indifference to incongruous counterparts. Nor is there any system of value associations with the left and the right. The Tenejapan evidence that speaks to these Kantian themes points in two directions: (a) Kant was wrong to think that the structure of spatial regions founded on the human frame, and in particular the distinctions based on left and right, are in some sense essential human intuitions; (b) Kant may have been right to think that the left/right opposition, the perception of enantiomorphs, clockwiseness, East-West dichotomies, etc., are intimately connected to an overall system of spatial conception.

Abstract

The evolution of language and spatial cognition may have been deeply interconnected. The argument
goes as follows: 1. Human native spatial abilities are poor, but we make up for it with linguistic
and cultural prostheses; 2. The explanation for the loss of native spatial abilities may be
that language has cannibalized the hippocampus, the mammalian mental ‘GPS’; 3. Consequently,
language may have borrowed conceptual primitives from spatial cognition (in line with ‘localism’),
these being differentially combined in different languages; 4. The hippocampus may have
been colonized because: (a) space was prime subject matter for communication, (b) gesture uses
space to represent space, and was likely precursor to language. In order to explain why the other
great apes haven’t gone in the same direction, we need to invoke other factors, notably the ‘interaction
engine’, the ensemble of interactional abilities that make cooperative communication possible
and provide the matrix for the evolution and learning of language.

Abstract

Philosophers, psychologists, and linguists have argued that spatial conception is pivotal to cognition in general, providing a general, egocentric, and universal framework for cognition as well as metaphors for conceptualizing many other domains. But in an aboriginal community in Northern Queensland, a system of cardinal directions informs not only language, but also memory for arbitrary spatial arrays and directions. This work suggests that fundamental cognitive parameters, like the system of coding spatial locations, can vary cross-culturally, in line with the language spoken by a community. This opens up the prospect of a fruitful dialogue between anthropology and the cognitive sciences on the complex interaction between cultural and universal factors in the constitution of mind.

Abstract

The present study investigates the construction with help followed by the bare or to-infinitive in seven varieties of web-based English from Australia, Ghana, Great Britain, Hong Kong, India, Jamaica and the USA. In addition to various factors known from the literature, such as register, minimization of cognitive complexity and avoidance of identity (horror aequi), it studies the effect of predictability of the infinitive given help and the other way round on the language user’s choice between the constructional variants. These probabilistic constraints are tested in a series of Bayesian generalized additive mixed-effects regression models. The results demonstrate that the to-infinitive is particularly frequent in contexts with low predictability, or, in information-theoretic terms, with high information content. This tendency is interpreted as communicatively efficient behaviour, when more predictable units of discourse get less formal marking, and less predictable ones get more formal marking. However, the strength, shape and directionality of predictability effects exhibit variation across the countries, which demonstrates the importance of the cross-lectal perspective in research on communicative efficiency and other universal functional principles.

Abstract

The present paper discusses the benefits and challenges of token-based typology, which takes into account the frequencies of words and constructions in language use. This approach makes it possible to introduce new criteria for language classification, which would be difficult or impossible to achieve with the traditional, type-based approach. This point is illustrated by several quantitative studies of word order variation, which can be measured as entropy at different levels of granularity. I argue that this variation can be explained by general functional mechanisms and pressures, which manifest themselves in language use, such as optimization of processing (including avoidance of ambiguity) and grammaticalization of predictable units occurring in chunks. The case studies are based on multilingual corpora, which have been parsed using the Universal Dependencies annotation scheme.

Abstract

Reinstatement of memory-related neural activity measured with high temporal precision potentially provides a useful index for real-time monitoring of the timing of activation of memory content during cognitive processing. The utility of such an index extends to any situation where one is interested in the (relative) timing of activation of different sources of information in memory, a paradigm case of which is tracking lexical activation during language processing. Essential for this approach is that memory reinstatement effects are robust, so that their absence (in the average) definitively indicates that no lexical activation is present. We used electroencephalography to test the robustness of a reported subsequent memory finding involving reinstatement of frequency-specific entrained oscillatory brain activity during subsequent recognition. Participants learned lists of words presented on a background flickering at either 6 or 15 Hz to entrain a steady-state brain response. Target words subsequently presented on a non-flickering background that were correctly identified as previously seen exhibited reinstatement effects at both entrainment frequencies. Reliability of these statistical inferences was however critically dependent on the approach used for multiple comparisons correction. We conclude that effects are not robust enough to be used as a reliable index of lexical activation during language processing.

Abstract

Schizophrenia is a common and complex mental disorder with neuroimaging alterations. Recent neuroanatomical pattern recognition studies attempted to distinguish individuals with schizophrenia by structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI). 1, 2 Applications of cutting-edge machine learning approaches in structural neuroimaging studies have revealed potential pathways to classification of schizophrenia based on regional gray matter volume (GMV) or density or cortical thickness. 3–5 Additionally, cortical folding may have high discriminatory value in correctly identifying symptom severity in schizophrenia. 6 Regional GMV and cortical thickness have also been combined in attempts to differentiate individuals with schizophrenia from healthy controls (HCs). 7 Applications of machine learning algorithms to diffusion imaging data analysis to predict individuals with first-episode schizophrenia (FES) have achieved encouraging accuracy. 8–10 White matter (WM) abnormalities in schizophrenia as estimated by DTI appear to be present in the early stage of the disorder, most likely reflecting the developmental stage of the sample of interest.

Abstract

Neurocognitive deficits are frequently observed in patients with schizophrenia and major depressive disorder (MDD). The relations between cognitive features may be represented by neurocognitive graphs based on cognitive features, modeled as Gaussian Markov random fields. However, it is unclear whether it is possible to differentiate between phenotypic patterns associated with the differential diagnosis of schizophrenia and depression using this neurocognitive graph approach. In this study, we enrolled 215 first-episode patients with schizophrenia (FES), 125 with MDD, and 237 demographically-matched healthy controls (HCs). The cognitive performance of all participants was evaluated using a battery of neurocognitive tests. The graphical LASSO model was trained with a one-vs-one scenario to learn the conditional independent structure of neurocognitive features of each group. Participants in the holdout dataset were classified into different groups with the highest likelihood. A partial correlation matrix was transformed from the graphical model to further explore the neurocognitive graph for each group. The classification approach identified the diagnostic class for individuals with an average accuracy of 73.41% for FES vs HC, 67.07% for MDD vs HC, and 59.48% for FES vs MDD. Both of the neurocognitive graphs for FES and MDD had more connections and higher node centrality than those for HC. The neurocognitive graph for FES was less sparse and had more connections than that for MDD. Thus, neurocognitive graphs based on cognitive features are promising for describing endophenotypes that may discriminate schizophrenia from depression.

Abstract

Identifying data-driven biotypes of major depressive disorder (MDD) has promise for the clarification of diagnostic heterogeneity. However, few studies have focused on white-matter abnormalities for MDD subtyping. This study included 116 patients with MDD and 118 demographically-matched healthy controls assessed by diffusion tensor imaging and neurocognitive evaluation. Hierarchical clustering was applied to the major fiber tracts, in conjunction with tract-based spatial statistics, to reveal white-matter alterations associated with MDD. Clinical and neurocognitive differences were compared between identified subgroups and healthy controls. With fractional anisotropy extracted from 20 fiber tracts, cluster analysis revealed 3 subgroups based on the patterns of abnormalities. Patients in each subgroup versus healthy controls showed a stepwise pattern of white-matter alterations as follows: subgroup 1 (25.9% of patient sample), widespread white-matter disruption; subgroup 2 (43.1% of patient sample), intermediate and more localized abnormalities in aspects of the corpus callosum and left cingulate; and subgroup 3 (31.0% of patient sample), possible mild alterations, but no statistically significant tract disruption after controlling for family-wise error. The neurocognitive impairment in each subgroup accompanied the white-matter alterations: subgroup 1, deficits in sustained attention and delayed memory; subgroup 2, dysfunction in delayed memory; and subgroup 3, no significant deficits. Three subtypes of white-matter abnormality exist in individuals with major depression, those having widespread abnormalities suffering more neurocognitive impairments, which may provide evidence for parsing the heterogeneity of the disorder and help optimize type-specific treatment approaches.

Abstract

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10−8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

Abstract

Verb learning is important for young children. While most
previous research has focused on linguistic and conceptual
challenges in early verb learning (e.g. Gentner, 1982, 2006),
the present paper examined early verb learning at the
attentional level and quantified the input for early verb learning
by measuring verb-action co-occurrence statistics in parent-
child interaction from the learner’s perspective. To do so, we
used head-mounted eye tracking to record fine-grained
multimodal behaviors during parent-infant joint play, and
analyzed parent speech, parent and infant action, and infant
attention at the moments when parents produced verb labels.
Our results show great variability across different action verbs,
in terms of frequency of verb utterances, frequency of
corresponding actions related to verb meanings, and infants’
attention to verbs and actions, which provide new insights on
why some verbs are harder to learn than others.

Abstract

Reading is an important high‐level cognitive function of the human brain, requiring interaction among multiple brain regions. Revealing differences between children's large‐scale functional brain networks for reading tasks and those of adults helps us to understand how the functional network changes over reading development. Here we used functional magnetic resonance imaging data of 17 adults (19–28 years old) and 16 children (11–13 years old), and graph theoretical analyses to investigate age‐related changes in large‐scale functional networks during rhyming and meaning judgment tasks on pairs of visually presented Chinese characters. We found that: (1) adults had stronger inter‐regional connectivity and nodal degree in occipital regions, while children had stronger inter‐regional connectivity in temporal regions, suggesting that adults rely more on visual orthographic processing whereas children rely more on auditory phonological processing during reading. (2) Only adults showed between‐task differences in inter‐regional connectivity and nodal degree, whereas children showed no task differences, suggesting the topological organization of adults’ reading network is more specialized. (3) Children showed greater inter‐regional connectivity and nodal degree than adults in multiple subcortical regions; the hubs in children were more distributed in subcortical regions while the hubs in adults were more distributed in cortical regions. These findings suggest that reading development is manifested by a shift from reliance on subcortical to cortical regions. Taken together, our study suggests that Chinese reading development is supported by developmental changes in brain connectivity properties, and some of these changes may be domain‐general while others may be specific to the reading domain.

Abstract

Fundamental human traits, such as language and bipedalism, are associated with a range of anatomical adaptations in craniofacial shaping and skeletal remodeling. However, it is unclear how such morphological features arose during hominin evolution. FOXP2 is a brain-expressed transcription factor implicated in a rare disorder involving speech apraxia and language impairments. Analysis of its evolutionary history suggests that this gene may have contributed to the emergence of proficient spoken language. In the present study, through analyses of skeleton-specific knockout mice, we identified roles of Foxp2 in skull shaping and bone remodeling. Selective ablation of Foxp2 in cartilage disrupted pup vocalizations in a similar way to that of global Foxp2 mutants, which may be due to pleiotropic effects on craniofacial morphogenesis. Our findings also indicate that Foxp2 helps to regulate strength and length of hind limbs and maintenance of joint cartilage and intervertebral discs, which are all anatomical features that are susceptible to adaptations for bipedal locomotion. In light of the known roles of Foxp2 in brain circuits that are important for motor skills and spoken language, we suggest that this gene may have been well placed to contribute to coevolution of neural and anatomical adaptations related to speech and bipedal locomotion.

Abstract

Studies exploring the influence of executive functions (EF) on perspective-taking have focused on inhibition and working memory in young adults or clinical populations. Less consideration has been given to more complex capacities that also involve switching attention between perspectives, or to changes in EF and concomitant effects on perspective-taking across the lifespan. To address this, we assessed whether individual differences in inhibition and attentional switching in healthy adults (ages 17–84) predict performance on a task in which speakers identified targets for a listener with size-contrasting competitors in common or privileged ground. Modification differences across conditions decreased with age. Further, perspective taking interacted with EF measures: youngest adults’ sensitivity to perspective was best captured by their inhibitory performance; oldest adults’ sensitivity was best captured by switching performance. Perspective-taking likely involves multiple aspects of EF, as revealed by considering a wider range of EF tasks and individual capacities across the lifespan.

Abstract

We present the Narrative Brain Dataset, an fMRI dataset that was collected during spoken presentation of short excerpts of three
stories in Dutch. Together with the brain imaging data, the dataset contains the written versions of the stimulation texts. The texts are
accompanied with stochastic (perplexity and entropy) and semantic computational linguistic measures. The richness and unconstrained
nature of the data allows the study of language processing in the brain in a more naturalistic setting than is common for fMRI studies.
We hope that by making NBD available we serve the double purpose of providing useful neural data to researchers interested in natural
language processing in the brain and to further stimulate data sharing in the field of neuroscience of language.

Abstract

In recent years, there has been renewed interest in the biological and cultural evolution of music, and specifically in the role played by perceptual and cognitive factors in shaping core features of musical systems, such as melody, harmony, and rhythm. One proposal originates in the language sciences. It holds that aspects of musical systems evolve by adapting gradually, in the course of successive generations, to the structural and functional characteristics of the sensory and memory systems of learners and “users” of music. This hypothesis has found initial support in laboratory experiments on music transmission. In this article, we first review some of the most important theoretical and empirical contributions to the field of music evolution. Next, we identify a major current limitation of these studies, i.e., the lack of direct neural support for the hypothesis of cognitive adaptation. Finally, we discuss a recent experiment in which this issue was addressed by using event-related potentials (ERPs). We suggest that the introduction of neurophysiology in cultural transmission research may provide novel insights on the micro-evolutionary origins of forms of variation observed in cultural systems.

Abstract

Name signs are based on descriptions, initialization, and loan translations. Nyst and Baker (2003) have found crosslinguistic similarities in the phonology of name signs, such as a preference for one-handed signs and for the head location. Studying Kata Kolok (KK), a rural sign language without indigenous fingerspelling, strongly suggests that one-handedness is not correlated to initialization, but represents a more general feature of name sign phonology. Like in other sign languages, the head location is used frequently in both KK and Sign Language of the Netherlands (NGT) name signs. The use of nonmanuals, however, is strikingly different. NGT name signs are always accompanied by mouthings, which are absent in KK. Instead, KK name signs may use mouth gestures; these may disambiguate manually identical name signs, and even form independent name signs without any manual features

Abstract

Continuous Bag of Words (CBOW) is a powerful text embedding method. Due to its strong capabilities to encode word content, CBOW embeddings perform well on a wide range of downstream tasks while being efficient to compute. However, CBOW is not capable of capturing the word order. The reason is that the computation of CBOW's word embeddings is commutative, i.e., embeddings of XYZ and ZYX are the same. In order to address this shortcoming, we propose a
learning algorithm for the Continuous Matrix Space Model, which we call Continual Multiplication of Words (CMOW). Our algorithm is an adaptation of word2vec, so that it can be trained on large quantities of unlabeled text. We empirically show that CMOW better captures linguistic properties, but it is inferior to CBOW in memorizing word content. Motivated by these findings, we propose a hybrid model that combines the strengths of CBOW and CMOW. Our results show that the hybrid CBOW-CMOW-model retains CBOW's strong ability to memorize word content while at the same time substantially improving its ability to encode other linguistic information by 8%. As a result, the hybrid also performs better on 8 out of 11 supervised downstream tasks with an average improvement of 1.2%.

Abstract

For (semi-)automated subject indexing systems in digital libraries, it is often more practical to use metadata such as the title of a publication instead of the full-text or the abstract. Therefore, it is desirable to have good text mining and text classification algorithms that operate well already on the title of a publication. So far, the classification performance on titles is not competitive with the performance on the full-texts if the same number of training samples is used for training. However, it is much easier to obtain title data in large quantities and to use it for training than full-text data. In this paper, we investigate the question how models obtained from training on increasing amounts of title training data compare to models from training on a constant number of full-texts. We evaluate this question on a large-scale dataset from the medical domain (PubMed) and from economics (EconBiz). In these datasets, the titles and annotations of millions of publications are available, and they outnumber the available full-texts by a factor of 20 and 15, respectively. To exploit these large amounts of data to their full potential, we develop three strong deep learning classifiers and evaluate their performance on the two datasets. The results are promising. On the EconBiz dataset, all three classifiers outperform their full-text counterparts by a large margin. The best title-based classifier outperforms the best full-text method by 9.4%. On the PubMed dataset, the best title-based method almost reaches the performance of the best full-text classifier, with a difference of only 2.9%.

Abstract

Is there a universal hierarchy of the senses, such that some senses (e.g., vision) are more accessible to consciousness and linguistic description than others (e.g., smell)? The long-standing presumption in Western thought has been that vision and audition are more objective than the other senses, serving as the basis of knowledge and understanding, whereas touch, taste, and smell are crude and of little value. This predicts that humans ought to be better at communicating about sight and hearing than the other senses, and decades of work based on English and related languages certainly suggests this is true. However, how well does this reflect the diversity of languages and communities worldwide? To test whether there is a universal hierarchy of the senses, stimuli from the five basic senses were used to elicit descriptions in 20 diverse languages, including 3 unrelated sign languages. We found that languages differ fundamentally in which sensory domains they linguistically code systematically, and how they do so. The tendency for better coding in some domains can be explained in part by cultural preoccupations. Although languages seem free to elaborate specific sensory domains, some general tendencies emerge: for example, with some exceptions, smell is poorly coded. The surprise is that, despite the gradual phylogenetic accumulation of the senses, and the imbalances in the neural tissue dedicated to them, no single hierarchy of the senses imposes itself upon language.

Abstract

People struggle to name odors, but this
limitation is not universal. Majid and
Kruspe investigate whether superior
olfactory performance is due to
subsistence, ecology, or language family.
By comparing closely related
communities in the Malay Peninsula, they
find that only hunter-gatherers are
proficient odor namers, suggesting that
subsistence is crucial.

Abstract

What is the relationship between the language we speak and the way we think? Researchers working at the interface of language and cognition hope to understand the complex interplay between linguistic structures and the way the mind works. This is thorny territory in anthropology and its closely allied disciplines, such as linguistics and psychology.

Abstract

Olfaction presents a particularly interesting arena to explore abstraction in language. Like other abstract domains, such as time, odours can be difficult to conceptualize. An odour cannot be seen or held, it can be difficult to locate in space, and for most people odours are difficult to verbalize. On the other hand, odours give rise to primary sensory experiences. Every time we inhale we are using olfaction to make sense of our environment. We present new experimental data from 30 Jahai hunter-gatherers from the Malay Peninsula and 30 matched Dutch participants from the Netherlands in an odour naming experiment. Participants smelled monomolecular odorants and named odours while reaction times, odour descriptors and facial expressions were measured. We show that while Dutch speakers relied on concrete descriptors, i.e. they referred to odour sources (e.g. smells like lemon), the Jahai used abstract vocabulary to name the same odours (e.g. musty). Despite this differential linguistic categorization, analysis of facial expressions showed that the two groups, nevertheless, had the same initial emotional reactions to odours. Critically, these cross-cultural data present a challenge for how to think about abstraction in language.

Abstract

People engage in simulation when reading literary narratives. In this study, we tried to pinpoint how different kinds of simulation (perceptual and motor simulation, mentalising) affect reading behaviour. Eye-tracking (gaze durations, regression probability) and questionnaire data were collected from 102 participants, who read three literary short stories. In a pre-test, 90 additional participants indicated which parts of the stories were high in one of the three kinds of simulation-eliciting content. The results show that motor simulation reduces gaze duration (faster reading), whereas perceptual simulation and mentalising increase gaze duration (slower reading). Individual differences in the effect of simulation on gaze duration were found, which were related to individual differences in aspects of story world absorption and story appreciation. These findings suggest fundamental differences between different kinds of simulation and confirm the role of simulation in absorption and appreciation.

Abstract

Studies have claimed that blind people’s spatial representations are different from sighted people, and blind people display superior auditory processing. Due to the nature of auditory and haptic information, it has been proposed that blind people have spatial representations that are more sequential than sighted people. Even the temporary loss of sight—such as through blindfolding—can affect spatial representations, but not much research has been done on this topic. We compared blindfolded and sighted people’s linguistic spatial expressions and non-linguistic localization accuracy to test how blindfolding affects the representation of path in auditory motion events. We found that blindfolded people were as good as sighted people when localizing simple sounds, but they outperformed sighted people when localizing auditory motion events. Blindfolded people’s path related speech also included more sequential, and less holistic elements. Our results indicate that even temporary loss of sight influences spatial representations of auditory motion events

Abstract

Boundary extension (BE) is a memory error in which observers remember more of a scene than they actually viewed. This error reflects one’s prediction that a scene naturally continues and is driven by scene schema and contextual knowledge. In two separate experiments we investigated the necessity of context and scene schema in BE. In Experiment 1, observers viewed scenes that either contained semantically consistent or inconsistent objects as well as objects on white backgrounds. In both types of scenes and in the no-background condition there was a BE effect; critically, semantic inconsistency in scenes reduced the magnitude of BE. In Experiment 2 when we used abstract shapes instead of meaningful objects, there was no BE effect. We suggest that although scene schema is necessary to elicit BE, contextual consistency is not required.

Abstract

Prior knowledge about the visual world can change how a visual stimulus is processed. Two forms of prior knowledge are often distinguished: stimulus familiarity (i.e., whether a stimulus has been seen before) and stimulus expectation (i.e., whether a stimulus is expected to occur, based on the context). Neurophysiological studies in monkeys have shown suppression of spiking activity both for expected and for familiar items in object-selective inferotemporal cortex. It is an open question, however, if and how these types of knowledge interact in their modulatory effects on the sensory response. To address this issue and to examine whether previous findings generalize to noninvasively measured neural activity in humans, we separately manipulated stimulus familiarity and expectation while noninvasively recording human brain activity using magnetoencephalography. We observed independent suppression of neural activity by familiarity and expectation, specifically in the lateral occipital complex, the putative human homologue of monkey inferotemporal cortex. Familiarity also led to sharpened response dynamics, which was predominantly observed in early visual cortex. Together, these results show that distinct types of sensory knowledge jointly determine the amount of neural resources dedicated to object processing in the visual ventral stream.

Abstract

Background

Autism is a dimensional condition, representing the extreme end of a continuum of social competence that extends throughout the general population. Currently, little is known about how autistic social traits (ASTs), measured across the full spectrum of severity, develop during childhood and adolescence, including whether there are developmental differences between boys and girls. Therefore, we sought to chart the trajectories of ASTs in the general population across childhood and adolescence, with a focus on gender differences.
Methods

Participants were 9,744 males (n = 4,784) and females (n = 4,960) from ALSPAC, a UK birth cohort study. ASTs were assessed when participants were aged 7, 10, 13 and 16 years, using the parent‐report Social Communication Disorders Checklist. Data were modelled using latent growth curve analysis.
Results

Developmental trajectories of males and females were nonlinear, showing a decline from 7 to 10 years, followed by an increase between 10 and 16 years. At 7 years, males had higher levels of ASTs than females (mean raw score difference = 0.88, 95% CI [.72, 1.04]), and were more likely (odds ratio [OR] = 1.99; 95% CI, 1.82, 2.16) to score in the clinical range on the SCDC. By 16 years this gender difference had disappeared: males and females had, on average, similar levels of ASTs (mean difference = 0.00, 95% CI [−0.19, 0.19]) and were equally likely to score in the SCDC's clinical range (OR = 0.91, 95% CI, 0.73, 1.10). This was the result of an increase in females’ ASTs between 10 and 16 years.
Conclusions

There are gender‐specific trajectories of autistic social impairment, with females more likely than males to experience an escalation of ASTs during early‐ and midadolescence. It remains to be discovered whether the observed female adolescent increase in ASTs represents the genuine late onset of social difficulties or earlier, subtle, pre‐existing difficulties becoming more obvious.

Abstract

Prediction of upcoming input is thought to be a main characteristic of language processing (e.g. Altmann & Mirkovic, 2009; Dell & Chang, 2014; Federmeier, 2007; Ferreira & Chantavarin, 2018; Pickering & Gambi, 2018; Hale, 2001; Hickok, 2012; Huettig 2015; Kuperberg & Jaeger, 2016; Levy, 2008; Norris, McQueen, & Cutler, 2016; Pickering & Garrod, 2013; Van Petten & Luka, 2012). One of the main pillars of experimental support for this notion comes from studies that have attempted to measure electrophysiological markers of prediction when participants read or listened to sentences ending in highly predictable words. The N400, a negative-going and centro-parietally distributed component of the ERP occurring approximately 400ms after (target) word onset, has been frequently interpreted as indexing prediction of the word (or the semantic representations and/or the phonological form of the predicted word, see Kutas & Federmeier, 2011; Nieuwland, 2019; Van Petten & Luka, 2012; for review). A major difficulty for interpreting N400 effects in language processing however is that it has been difficult to establish whether N400 target word modulations conclusively reflect prediction rather than (at least partly) ease of integration. In the present exploratory study, we attempted to distinguish lexical prediction (i.e. ‘top-down’ activation) from lexical integration (i.e. ‘bottom-up’ activation) accounts of ERP N400 modulations in language processing.

Abstract

Lombard speech, speech produced in noise, is acoustically different from speech produced in quiet (plain speech) in several ways, including having a higher and wider F0 range (pitch). Extensive research on native Lombard speech does not consider that non-natives experience a higher cognitive load while producing
speech and that the native language may influence the non-native speech. We investigated pitch range in plain and Lombard speech in native and non-natives.
Dutch and American-English speakers read contrastive question-answer pairs in quiet and in noise in English, while the Dutch also read Dutch sentence pairs. We found that Lombard speech is characterized by a wider pitch range than plain speech, for all speakers (native English, non-native English, and native Dutch).
This shows that non-natives also widen their pitch range in Lombard speech. In sentences with early-focus, we see the same increase in pitch range when going from plain to Lombard speech in native and non-native English, but a smaller increase in native Dutch. In sentences with late-focus, we see the biggest increase for the native English, followed by non-native English and then native Dutch. Together these results indicate an effect of the native language on non-native Lombard speech.

Abstract

Lombard speech, speech produced in noise, is
typically produced with a higher fundamental
frequency (F0, pitch) compared to speech in quiet. This paper examined the potential differences in native and non-native Lombard speech by analyzing median pitch in sentences with early- or late-focus produced in quiet and noise. We found an increase in pitch in late-focus sentences in noise for Dutch speakers in both English and Dutch, and for American-English speakers in English. These results
show that non-native speakers produce Lombard speech, despite their higher cognitive load. For the early-focus sentences, we found a difference between the Dutch and the American-English speakers. Whereas the Dutch showed an increased F0 in noise
in English and Dutch, the American-English speakers did not in English. Together, these results suggest that some acoustic characteristics of Lombard speech, such as pitch, may be language-specific, potentially
resulting in the native language influencing the non-native Lombard speech.

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

Human thought and language have extraordinary expressive power because meaningful parts can be assembled into more complex semantic structures. This partly underlies our ability to compose meanings into endlessly novel configurations, and sets us apart from other species and current computing devices. Crucially, human behaviour, including language use and linguistic data, indicates that composing parts into complex structures does not threaten the existence of constituent parts as independent units in the system: parts and wholes exist simultaneously yet independently from one another in the mind and brain. This independence is evident in human behaviour, but it seems at odds with what is known about the brain's exquisite sensitivity to statistical patterns: everyday language use is productive and expressive precisely because it can go beyond statistical regularities. Formal theories in philosophy and linguistics explain this fact by assuming that language and thought are compositional: systems of representations that separate a variable (or role) from its values (fillers), such that the meaning of a complex expression is a function of the values assigned to the variables. The debate on whether and how compositional systems could be implemented in minds, brains and machines remains vigorous. However, it has not yet resulted in mechanistic models of semantic composition: how, then, are the constituents of thoughts and sentences put and held together? We review and discuss current efforts at understanding this problem, and we chart possible routes for future research.

Abstract

Neither neurobiological nor process models of meaning composition specify the operator through which constituent parts are bound together into compositional structures. In this paper, we argue that a neurophysiological computation system cannot achieve the compositionality exhibited in human thought and language if it were to rely on a multiplicative operator to perform binding, as the tensor product (TP)-based systems that have been widely adopted in cognitive science, neuroscience and artificial intelligence do. We show via simulation and two behavioural experiments that TPs violate variable-value independence, but human behaviour does not. Specifically, TPs fail to capture that in the statements fuzzy cactus and fuzzy penguin, both cactus and penguin are predicated by fuzzy(x) and belong to the set of fuzzy things, rendering these arguments similar to each other. Consistent with that thesis, people judged arguments that shared the same role to be similar, even when those arguments themselves (e.g., cacti and penguins) were judged to be dissimilar when in isolation. By contrast, the similarity of the TPs representing fuzzy(cactus) and fuzzy(penguin) was determined by the similarity of the arguments, which in this case approaches zero. Based on these results, we argue that neural systems that use TPs for binding cannot approximate how the human mind and brain represent compositional information during processing. We describe a contrasting binding mechanism that any physiological or artificial neural system could use to maintain independence between a role and its argument, a prerequisite for compositionality and, thus, for instantiating the expressive power of human thought and language in a neural system.

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

Humans learn to represent complex structures (e.g. natural language, music, mathematics) from experience with their environments. Often such structures are latent, hidden, or not encoded in statistics about sensory representations alone. Accounts of human cognition have long emphasized the importance of structured representations, yet the majority of contemporary neural networks do not learn structure from experience. Here, we describe one way that structured, functionally symbolic representations can be instantiated in an artificial neural network. Then, we describe how such latent structures (viz. predicates) can be learned from experience with unstructured data. Our approach exploits two principles from psychology and neuroscience: comparison of representations, and the naturally occurring dynamic properties of distributed computing across neuronal assemblies (viz. neural oscillations). We discuss how the ability to learn predicates from experience, to represent information compositionally, and to extrapolate knowledge to unseen data is core to understanding and modeling the most complex human behaviors (e.g. relational reasoning, analogy, language processing, game play).

Abstract

Active communication between researchers and society is necessary for the scientific community’s involvement in developing sciencebased
policies. This need is recognized by governmental and funding agencies that compel scientists to increase their public engagement
and disseminate research findings in an accessible fashion. Storytelling techniques can help convey science by engaging people’s imagination
and emotions. Yet, many researchers are uncertain about how to approach scientific storytelling, or feel they lack the tools to
undertake it. Here we explore some of the techniques intrinsic to crafting scientific narratives, as well as the reasons why scientific
storytellingmaybe an optimal way of communicating research to nonspecialists.Wealso point out current communication gaps between
science and society, particularly in the context of neurodiverse audiences and those that include neurological and psychiatric patients.
Present shortcomings may turn into areas of synergy with the potential to link neuroscience education, research, and advocacy

Abstract

Listeners are known to track statistical regularities in speech. Yet, which temporal cues
are encoded is unclear. This study tested effects of talker-specific habitual speech rate
and talker-independent average speech rate (heard over a longer period of time) on
the perception of the temporal Dutch vowel contrast /A/-/a:/. First, Experiment 1
replicated that slow local (surrounding) speech contexts induce fewer long /a:/
responses than faster contexts. Experiment 2 tested effects of long-term habitual
speech rate. One high-rate group listened to ambiguous vowels embedded in `neutral'
speech from talker A, intermixed with speech from fast talker B. Another low-rate group
listened to the same `neutral' speech from talker A, but to talker B being slow.
Between-group comparison of the `neutral' trials showed that the high-rate group
demonstrated a lower proportion of /a:/ responses, indicating that talker A's habitual
speech rate sounded slower when B was faster. In Experiment 3, both talkers
produced speech at both rates, removing the different habitual speech rates of talker A
and B, while maintaining the average rate differing between groups. This time no
global rate effect was observed. Taken together, the present experiments show that a
talker's habitual rate is encoded relative to the habitual rate of another talker, carrying
implications for episodic and constraint-based models of speech perception.

Abstract

Speech can be produced at different rates. Listeners take this rate variation into account by normalizing vowel duration for contextual speech rate: An ambiguous Dutch word /m?t/ is perceived as short /mAt/ when embedded in a slow context, but long /ma:t/ in a fast context. Whilst some have argued that this rate normalization involves low-level automatic perceptual processing, there is also evidence that it arises at higher-level cognitive processing stages, such as decision making. Prior research on rate-dependent speech perception has only used explicit recognition tasks to investigate the phenomenon, involving both perceptual processing and decision making. This study tested whether speech rate normalization can be observed without explicit decision making, using a cross-modal repetition priming paradigm. Results show that a fast precursor sentence makes an embedded ambiguous prime (/m?t/) sound (implicitly) more /a:/-like, facilitating lexical access to the long target word "maat" in a (explicit) lexical decision task. This result suggests that rate normalization is automatic, taking place even in the absence of an explicit recognition task. Thus, rate normalization is placed within the realm of everyday spoken conversation, where explicit categorization of ambiguous sounds is rare.

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

Poor recognition of other-race faces is ubiquitous around the world. We resolve a longstanding contradiction in the literature concerning whether interracial social contact improves the other-race effect. For the first time, we measure the age at which contact was experienced. taking advantage of
unusual demographics allowing dissociation of childhood from adult contact, results show sufficient childhood contact eliminated poor other-race recognition altogether (confirming inter-country adoption
studies). Critically, however, the developmental window for easy acquisition of other-race faces closed by approximately 12 years of age and social contact as an adult — even over several years and involving many other-race friends — produced no improvement. Theoretically, this pattern of developmental change in plasticity mirrors that found in language, suggesting a shared origin grounded in the
functional importance of both skills to social communication. Practically, results imply that, where parents wish to ensure their offspring develop the perceptual skills needed to recognise other-race people easily, childhood experience should be encouraged: just as an English-speaking person who moves to France as a child (but not an adult) can easily become a native speaker of French, we can easily
become “native recognisers” of other-race faces via natural social exposure obtained in childhood, but not later

Abstract

Although word boundaries are rarely clearly marked, listeners can rapidly recognize the individual words of spoken sentences. Some theories explain this in terms of competition between multiply activated lexical hypotheses; others invoke sensitivity to prosodic structure. We describe a connectionist model, SHORTLIST, in which recognition by activation and competition is successful with a realistically sized lexicon. Three experiments are then reported in which listeners detected real words embedded in nonsense strings, some of which were themselves the onsets of longer words. Effects both of competition between words and of prosodic structure were observed, suggesting that activation and competition alone are not sufficient to explain word recognition in continuous speech. However, the results can be accounted for by a version of SHORTLIST that is sensitive to prosodic structure.

Abstract

Several models of spoken word recognition postulate that recognition is achieved via a process of competition between lexical hypotheses. Competition not only provides a mechanism for isolated word recognition, it also assists in continuous speech recognition, since it offers a means of segmenting continuous input into individual words. We present statistics on the pattern of occurrence of words embedded in the polysyllabic words of the English vocabulary, showing that an overwhelming majority (84%) of polysyllables have shorter words embedded within them. Positional analyses show that these embeddings are most common at the onsets of the longer word. Although both phonological and syntactic constraints could rule out some embedded words, they do not remove the problem. Lexical competition provides a means of dealing with lexical embedding. It is also supported by a growing body of experimental evidence. We present results which indicate that competition operates both between word candidates that begin at the same point in the input and candidates that begin at different points (McQueen, Norris, & Cutler, 1994, Noms, McQueen, & Cutler, in press). We conclude that lexical competition is an essential component in models of continuous speech recognition.

Abstract

The results of a word-spotting experiment are presented in which Dutch listeners tried to spot different types of bisyllabic Dutch words embedded in different types of nonsense contexts. Embedded verbs were not reliably harder to spot than embedded nouns; this suggests that nouns and verbs are recognised via the same basic processes. Iambic words were no harder to spot than trochaic words, suggesting that trochaic words are not in principle easier to recognise than iambic words. Words were harder to spot in consonantal contexts (i.e., contexts which themselves could not be words) than in longer contexts which contained at least one vowel (i.e., contexts which, though not words, were possible words of Dutch). A control experiment showed that this difference was not due to acoustic differences between the words in each context. The results support the claim that spoken-word recognition is sensitive to the viability of sound sequences as possible words.

Abstract

Recurrent deletions of a ~600-kb region of 16p11.2 have been associated with a highly penetrant form of childhood apraxia of speech (CAS). Yet prior findings have been based on a small, potentially biased sample using retrospectively collected data. We examine the prevalence of CAS in a larger cohort of individuals with 16p11.2 deletion using a prospectively designed assessment battery. The broader speech and language phenotype associated with carrying this deletion was also examined. 55 participants with 16p11.2 deletion (47 children, 8 adults) underwent deep phenotyping to test for the presence of CAS and other speech and language diagnoses. Standardized tests of oral motor functioning, speech production, language, and non-verbal IQ were conducted. The majority of children (77%) and half of adults (50%) met criteria for CAS. Other speech outcomes were observed including articulation or phonological errors (i.e., phonetic and cognitive-linguistic errors, respectively), dysarthria (i.e., neuromuscular speech disorder), minimal verbal output, and even typical speech in some. Receptive and expressive language impairment was present in 73% and 70% of children, respectively. Co-occurring neurodevelopmental conditions (e.g., autism) and non-verbal IQ did not correlate with the presence of CAS. Findings indicate that CAS is highly prevalent in children with 16p11.2 deletion with symptoms persisting into adulthood for many. Yet CAS occurs in the context of a broader speech and language profile and other neurobehavioral deficits. Further research will elucidate specific genetic and neural pathways leading to speech and language deficits in individuals with 16p11.2 deletions, resulting in more targeted speech therapies addressing etiological pathways.

Abstract

Humans learn language by interaction with their environment and listening to other humans. It should also be possible for computational models to learn language directly from speech but so far most approaches require text. We improve on existing neural network approaches to create visually grounded embeddings for spoken utterances. Using a combination of a multi-layer GRU, importance sampling, cyclic learning rates, ensembling and vectorial self-attention our results show a remarkable increase in image-caption retrieval performance over previous work. Furthermore, we investigate which layers in the model learn to recognise words in the input. We find that deeper network layers are better at encoding word presence, although the final layer has slightly lower performance. This shows that our visually grounded sentence encoder learns to recognise words from the input even though it is not explicitly trained for word recognition.

Abstract

Current approaches to learning semantic representations of sentences often use prior word-level knowledge. The current study aims to leverage visual information in order to capture sentence level semantics without the need for word embeddings. We use a multimodal sentence encoder trained on a corpus of images with matching text captions to produce visually grounded sentence embeddings. Deep Neural Networks are trained to map the two modalities to a common embedding space such that for an image the corresponding caption can be retrieved and vice versa. We show that our model achieves results comparable to the current state of the art on two popular image-caption retrieval benchmark datasets: Microsoft Common Objects in Context (MSCOCO) and Flickr8k. We evaluate the semantic content of the resulting sentence embeddings using the data from the Semantic Textual Similarity (STS) benchmark task and show that the multimodal embeddings correlate well with human semantic similarity judgements. The system achieves state-of-the-art results on several of these benchmarks, which shows that a system trained solely on multimodal data, without assuming any word representations, is able to capture sentence level semantics. Importantly, this result shows that we do not need prior knowledge of lexical level semantics in order to model sentence level semantics. These findings demonstrate the importance of visual information in semantics.

Abstract

The ultimate goal of our research is to improve an existing speech-based computational model of human speech recognition on the task of simulating the role of fine-grained phonetic information in human speech processing. As part of this work we are investigating articulatory feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. Articulatory feature (AF) modelling of speech has received a considerable amount of attention in automatic speech recognition research. Different approaches have been used to build AF classifiers, most notably multi-layer perceptrons. Recently, deep neural networks have been applied to the task of AF classification. This paper aims to improve AF classification by investigating two different approaches: 1) investigating the usefulness of a deep Convolutional neural network (CNN) for AF classification; 2) integrating the Mel filtering operation into the CNN architecture. The results showed a remarkable improvement in classification accuracy of the CNNs over state-of-the-art AF classification results for Dutch, most notably in the minority classes. Integrating the Mel filtering operation into the CNN architecture did not further improve classification performance.

Abstract

Thirty years ago, Pim Levelt published Speaking. During the 10th International Workshop on Language Production held at the Max Planck Institute for Psycholinguistics in Nijmegen in July 2018, researchers reflected on the impact of the book in the field, developments since its publication, and current research trends. The contributions in this Special Issue are closely related to the presentations given at the workshop. In this editorial, we sketch the research agenda set by Speaking, review how different aspects of this agenda are taken up in the papers in this volume and outline directions for further research.

Abstract

Recently, a new theory of timing in sentence production has been proposed by Ferreira (1993). This theory assumes that at the phonological level, each syllable of an utterance is assigned one or more abstract timing units depending on its position in the prosodic structure. The number of timing units associated with a syllable determines the time interval between its onset and the onset of the next syllable. An interesting prediction from the theory, which was confirmed in Ferreira's experiments with speakers of American English, is that the time intervals between syllable onsets should only depend on the syllables' positions in the prosodic structure, but not on their segmental content. However, in the present experiments, which were carried out in Dutch, the intervals between syllable onsets were consistently longer for phonetically long syllables than for short syllables. The implications of this result for models of timing in sentence production are discussed.

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.