Publications

Abstract

Two types of phonological variation in Dutch, resulting from optional rules, are schwa epenthesis and schwa deletion. In a lexical decision experiment it was investigated whether the phonological variants were processed similarly to the standard forms. It was found that the two types of variation patterned differently. Words with schwa epenthesis were processed faster and more accurately than the standard forms, whereas words with schwa deletion led to less fast and less accurate responses. The results are discussed in relation to the role of consonant-vowel alternations in speech processing and the perceptual integrity of onset clusters.

Abstract

Like Einstein's general theory of relativity is concerned with explaining the basics of an observable experience – i.e., gravity – most people take for granted that Chomsky's theory of generative grammar (GG) is concerned with the basic nature of language. This chapter highlights a mere subset of central constructs in GG, showing how they have featured prominently and thus shaped formal linguistic studies in multilingualism. Because multilingualism includes a wide range of nonmonolingual populations, the constructs are divided across child bilingualism and adult third language for greater coverage. In the case of the former, the chapter examines how poverty of the stimulus has been investigated. Using the nascent field of L3/Ln acquisition as the backdrop, it discusses how the GG constructs of I-language versus E-language sit at the core of debates regarding the very notion of what linguistic transfer and mental representations should be taken to be.

Abstract

Mental imagery is a cognitive process crucial to human reasoning. Numerous studies have characterized specific
instances of this cognitive ability, as evoked by visual imagery (VI) or motor imagery (MI) tasks. However, it
remains unclear which neural resources are shared between VI and MI, and which are exclusively related to MI.
To address this issue, we have used fMRI to measure human brain activity during performance of VI and MI
tasks. Crucially, we have modulated the imagery process by manipulating the degree of mental rotation necessary
to solve the tasks. We focused our analysis on changes in neural signal as a function of the degree of mental
rotation in each task.

Abstract

In this paper we report on four experiments in which we attempted to prime the stress position of Dutch bisyllabic target nouns. These nouns, picture names, had stress on either the first or the second syllable. Auditory prime words had either the same stress as the target or a different stress (e.g., WORtel – MOtor vs. koSTUUM – MOtor; capital letters indicate stressed syllables in prime – target pairs). Furthermore, half of the prime words were semantically related, the other half were unrelated. In none of the experiments a stress priming effect was found. This could mean that stress is not stored in the lexicon. An additional finding was that targets with initial stress had a faster response than targets with a final stress. We hypothesize that bisyllabic words with final stress take longer to be encoded because this stress pattern is irregular with respect to the lexical distribution of bisyllabic stress patterns, even though it can be regular in terms of the metrical stress rules of Dutch.

Abstract

Recent research suggests that 12-month-old infants in German cultural settings have the motive of sharing their attention to and interest in various events with a social interlocutor. To do so, these preverbal infants predominantly use the pointing gesture (in this case the extended arm with or without extended index finger) as a means to direct another person’s attention. This task systematically investigates different types of motives underlying infants’ pointing. The occurrence of a protodeclarative (as opposed to protoimperative) motive is of particular interest because it requires an understanding of the recipient’s psychological states, such as attention and interest, that can be directed and accessed.

Abstract

There are three main strands of research which have investigated people’s intuitive knowledge of objects in motion. (1) Knowledge of the trajectories of objects in motion; (2) knowledge of the causes of motion; and (3) the categorisation of motion as to whether it has been produced by something animate or inanimate. We provide a brief introduction to each of these areas. We then point to some linguistic and cultural differences which may have consequences for people’s knowledge of objects in motion. Finally, we describe two experimental tasks and an ethnographic task that will allow us to collect data in order to establish whether, indeed, there are interesting cross-linguistic/cross-cultural differences in lay theories of objects in motion.

Abstract

Readers experience a number of sensations during reading. They do
not – or do not only – process words and sentences in a detached, abstract
manner. Instead they “perceive” what they read about. They see descriptions of
scenery, feel what characters feel, and hear the sounds in a story. These sensa-
tions tend to be grouped under the umbrella terms “mental simulation” and
“mental imagery.” This chapter provides an overview of empirical research on
the role of mental simulation during literary reading. Our chapter also discusses
what mental simulation is and how it relates to mental imagery. Moreover, it
explores how mental simulation plays a role in leading models of literary read-
ing and investigates under what circumstances mental simulation occurs dur-
ing literature reading. Finally, the effect of mental simulation on the literary
reader’s experience is discussed, and suggestions and unresolved issues in this
field are formulated.

Abstract

Visual and auditory channels have different affordances and
this is mirrored in what information is available for linguistic
encoding. The visual channel has high spatial acuity, whereas
the auditory channel has better temporal acuity. These
differences may lead to different conceptualizations of events
and affect multimodal language production. Previous studies of
motion events typically present visual input to elicit speech and
gesture. The present study compared events presented as audio-
only, visual-only, or multimodal (visual+audio) input and
assessed speech and co-speech gesture for path and manner of
motion in Turkish. Speakers with audio-only input mentioned
path more and manner less in verbal descriptions, compared to
speakers who had visual input. There was no difference in the
type or frequency of gestures across conditions, and gestures
were dominated by path-only gestures. This suggests that input
modality influences speakers’ encoding of path and manner of
motion events in speech, but not in co-speech gestures.

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 neural networks (RNNs) have long been an architecture of interest for computational models of human sentence processing. The recently introduced Transformer architecture outperforms RNNs on many natural language processing tasks but little is known about its ability to model human language processing. We compare Transformer- and RNN-based language models’ ability to account for measures of human reading effort. Our analysis shows Transformers to outperform RNNs in explaining self-paced reading times and neural activity during reading English sentences, challenging the widely held idea that human sentence processing involves recurrent and immediate processing and provides evidence for cue-based retrieval.

Abstract

This study addresses the question whether visually grounded speech recognition (VGS) models learn to capture sentence semantics without access to any prior linguistic knowledge. We produce synthetic and natural spoken versions of a well known semantic textual similarity database and show that our VGS model produces embeddings that correlate well with human semantic similarity judgements. Our results show that a model trained on a small image-caption database outperforms two models trained on much larger databases, indicating that database size is not all that matters. We also investigate the importance of having multiple captions per image and find that this is indeed helpful even if the total number of images is lower, suggesting that paraphrasing is a valuable learning signal. While the general trend in the field is to create ever larger datasets to train models on, our findings indicate other characteristics of the database can just as important.

Abstract

Language emergence is characterized by a high degree of lex-
ical variation. It has been suggested that the speed at which
lexical conventionalization occurs depends partially on social
structure. In large communities, individuals receive input from
many sources, creating a pressure for lexical convergence.
In small, insular communities, individuals can remember id-
iolects and share common ground with interlocuters, allow-
ing these communities to retain a high degree of lexical vari-
ation. We look at lexical variation in Kata Kolok, a sign lan-
guage which emerged six generations ago in a Balinese vil-
lage, where women tend to have more tightly-knit social net-
works than men. We test if there are differing degrees of lexical
uniformity between women and men by reanalyzing a picture
description task in Kata Kolok. We find that women’s produc-
tions exhibit less lexical uniformity than men’s. One possible
explanation of this finding is that women’s more tightly-knit
social networks allow for remembering idiolects, alleviating
the pressure for lexical convergence, but social network data
from the Kata Kolok community is needed to support this ex-
planation.

Abstract

The human language processor is conceived as a system that consists of several interrelated subsystems. Each subsystem performs a specific task in the complex process of language comprehension and production. A subsystem receives a particular input, performs certain specific operations on this input and yields a particular output. The subsystems can be characterized in terms of the transformations that relate the input representations to the output representations. An important issue in describing the language processing system is to identify the subsystems and to specify the relations between the subsystems. These relations can be conceived in two different ways. In one conception the subsystems are autonomous. They are related to each other only by the input-output channels. The operations in one subsystem are not affected by another system. The subsystems are modular, that is they are independent. In the other conception, the different subsystems influence each other. A subsystem affects the processes in another subsystem. In this conception there is an interaction between the subsystems.

Abstract

In this paper we describe a general scheme for internationalization of our talking head, Baldi, to speak other languages. We describe the modular structure of the auditory/visual synthesis software. As an example, we have created a synthetic Arabic talker, which is evaluated using a noisy word recognition task comparing this talker with a natural one.

Abstract

Demonstrative terms (e.g., this and that) are key items in understanding how a language constructs and interprets spatial relationships. This in-depth questionnaire explores how demonstratives (and similar spatial deixis forms) function in the research language, covering such topics as their morphology and syntax, semantic dimensions, and co-occurring gesture practices. Questionnaire responses should ideally be based on natural, situated discourse as well as elicitation with consultants.

Abstract

What are the preferred ways to describe spatial relationships in different linguistic and cultural groups, and how does this interact with non-linguistic spatial awareness? This game was devised as an interactive supplement to several items that collect information on the encoding and understanding of spatial relationships, especially as relevant to “route descriptions”. This is a director-matcher task, where one consultant has access to stimulus materials that shows a “target” situation, and directs another consultant (who cannot see the target) to recreate this arrangement.

Abstract

Conversation analysis (CA) is an approach to the study of language and social interaction that puts at center stage its sequential development. The chain of initiating and responding actions that characterizes any interaction is a source of internal evidence for the meaning of social behavior as it exposes the understandings that participants themselves give of what one another is doing. Such an analysis requires the close and repeated inspection of audio and video recordings of naturally occurring interaction, supported by transcripts and other forms of annotation. Distributional regularities are complemented by a demonstration of participants' orientation to deviant behavior. CA has long maintained a constructive dialogue and reciprocal influence with linguistic anthropology. This includes a recent convergence on the cross-linguistic and cross-cultural study of social interaction.

Abstract

The current version of the psycholinguistic model of human word recognition Shortlist suffers from two unrealistic constraints. First, the input of Shortlist must consist of a single string of phoneme symbols. Second, the current version of the search in Shortlist makes it difficult to deal with insertions and deletions in the input phoneme string. This research attempts to fully automatically derive a phoneme string from the acoustic signal that is as close as possible to the number of phonemes in the lexical representation of the word. We optimised an Automatic Phone Recogniser (APR) using two approaches, viz. varying the value of the mismatch parameter and optimising the APR output strings on the output of Shortlist. The approaches show that it will be very difficult to satisfy the input requirements of the present version of Shortlist with a phoneme string generated by an APR.

Abstract

We have recently developed a new model of human speech recognition, based on automatic speech recognition techniques [1]. The present paper has two goals. First, we show that the new model performs well in the recognition of lexically ambiguous input. These demonstrations suggest that the model is able to operate in the same optimal way as human listeners. Second, we discuss how to relate the behaviour of a recogniser, designed to discover the optimum path through a word lattice, to data from human listening experiments. We argue that this requires a metric that combines both path-based and word-based measures of recognition performance. The combined metric varies continuously as the input speech signal unfolds over time.

Abstract

Due to pronunciation variation, many insertions and deletions of phones occur in spontaneous speech. The psycholinguistic model of human speech recognition Shortlist is not well able to deal with phone insertions and deletions and is therefore not well suited for dealing with real-life input. The research presented in this paper explains how Shortlist can benefit from pronunciation variation modelling in dealing with real-life input. Pronunciation variation was modelled by including variants into the lexicon of Shortlist. A series of experiments was carried out to find the optimal acoustic model set for transcribing the training material that was used as basis for the generation of the variants. The Shortlist experiments clearly showed that Shortlist benefits from pronunciation variation modelling. However, the performance of Shortlist stays far behind the performance of other, more conventional speech recognisers.

Abstract

In this paper, we present a novel computational model of human speech recognition – called SpeM – based on the theory underlying Shortlist. We will show that SpeM, in combination with an automatic phone recogniser (APR), is able to simulate the human speech recognition process from the acoustic signal to the ultimate recognition of words. This joint model takes an acoustic speech file as input and calculates the activation flows of candidate words on the basis of the degree of fit of the candidate words with the input. Experiments showed that SpeM outperforms Shortlist on the recognition of ‘real-life’ input. Furthermore, SpeM performs only slightly worse than an off-the-shelf full-blown automatic speech recogniser in which all words are equally probable, while it provides a transparent computationally elegant paradigm for modelling word activations in human word recognition.

Abstract

The time course of metrical encoding, i.e. stress, during speech production is investigated. In a first experiment, participants were presented with pictures whose bisyllabic Dutch names had initial or final stress (KAno 'canoe' vs. kaNON 'cannon'; capital letters indicate stressed syllables). Picture names were matched for frequency and object recognition latencies. When participants were asked to judge whether picture names had stress on the first or second syllable, they showed significantly faster decision times for initially stressed targets than for targets with final stress. Experiment 2 replicated this effect with trisyllabic picture names (faster RTs for penultimate stress than for ultimate stress). In our view, these results reflect the incremental phonological encoding process. Wheeldon and Levelt (1995) found that segmental encoding is a process running from the beginning to the end of words. Here, we present evidence that the metrical pattern of words, i.e. stress, is also encoded incrementally.

Abstract

This study investigated the encoding of metrical information during speech production in Dutch. In Experiment 1, participants were asked to judge whether bisyllabic picture names had initial or final stress. Results showed significantly faster decision times for initially stressed targets (e.g., LEpel 'spoon') than for targets with final stress (e.g., liBEL 'dragon fly'; capital letters indicate stressed syllables) and revealed that the monitoring latencies are not a function of the picture naming or object recognition latencies to the same pictures. Experiments 2 and 3 replicated the outcome of the first experiment with bi- and trisyllabic picture names. These results demonstrate that metrical information of words is encoded rightward incrementally during phonological encoding in speech production. The results of these experiments are in line with Levelt's model of phonological encoding.

Abstract

The representative corpus SYN2000 in the Czech National Corpus (CNK) project containing 100 million word forms taken from different types of texts. I have tried to determine the extent and depth of the linguistic material in the corpus. First, I chose the adjectives indicating the basic colors of the spectrum and other parts of speech (names and adverbs) derived from these adjectives. An analysis of three examples - black, white and red - shows the extent of the linguistic wealth and diversity we are looking at: because of size limitations, no existing dictionary is capable of embracing all analyzed nuances. Currently, we can only hope that the next dictionary of contemporary Czech, built on the basis of the Czech National Corpus, will be electronic. Without the size limitations, we would be able us to include many of the fine nuances of language

Abstract

The basic idea behind this task is to find out how languages encode basic shape distinctions such as dimensionality, axial geometry, relative size, etc. More specifically, we want to find out (i) which formal means are used cross linguistically to encode basic shape distinctions, and (ii) which are the semantic distinctions that are made in this domain. In languages with many shape-classifiers, these distinctions are encoded (at least partially) in classifiers. In other languages, positional verbs, descriptive modifiers, such as “flat”, “round”, or nouns such as “cube”, “ball”, etc. might be the preferred means. In this context, we also want to investigate what other “grammatical work” shapeencoding expressions possibly do in a given language, e.g. unitization of mass nouns, or anaphoric uses of shape-encoding classifiers, etc. This task further seeks to determine the role of shape-related parameters which underlie the design of objects in the semantics of the system under investigation.