Publications

Abstract

In different fields of the humanities annotations of multimodal resources are a necessary component of the research workflow. Examples include linguistics, psychology, anthropology, etc. However, creation of those annotations is a very laborious task, which can take 50 to 100 times the length of the annotated media, or more. This can be significantly improved by applying innovative audio and video processing algorithms, which analyze the recordings and provide automated annotations. This is the aim of the AVATecH project, which is a collaboration of the Max Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS. In this paper we present a set of results of automated annotation together with an evaluation of their quality.

Abstract

Introduction Human spoken communication is multimodal, i.e. it encompasses both speech and gesture. Acoustic properties of voice, body movements, facial expression, etc. are an inherent and meaningful part of spoken interaction; they can provide attitudinal, grammatical and semantic information. In the recent years interest in audio-visual corpora has been rising rapidly as they enable investigation of different communicative modalities and provide more holistic view on communication (Kipp et al. 2009). Moreover, for some languages such corpora are the only available resource, as is the case for endangered languages for which no written resources exist.

Abstract

In this paper we describe audio and video processing algorithms that are developed in the scope of AVATecH project. The purpose of these algorithms is to shorten the time taken by manual annotation of audio and video recordings by extracting features from media files and creating semi-automated annotations. We show that the use of such supporting algorithms can shorten the annotation time to 30-50% of the time necessary to perform a fully manual annotation of the same kind.

Abstract

Languages differ in the degree of semantic flexibility of their syntactic roles. For example, Eng-
lish and Indonesian are considered more flexible with regard to the semantics of subjects,
whereas German and Japanese are less flexible. In Hawkins’ classification, more flexible lan-
guages are said to have a loose fit, and less flexible ones are those that have a tight fit. This
classification has been based on manual inspection of example sentences. The present paper
proposes a new, quantitative approach to deriving the measures of looseness and tightness from
corpora. We use corpora of online news from the Leipzig Corpora Collection in thirty typolog-
ically and genealogically diverse languages and parse them syntactically with the help of the
Universal Dependencies annotation software. Next, we compute Mutual Information scores for
each language using the matrices of lexical lemmas and four syntactic dependencies (intransi-
tive subjects, transitive subject, objects and obliques). The new approach allows us not only to
reproduce the results of previous investigations, but also to extend the typology to new lan-
guages. We also demonstrate that verb-final languages tend to have a tighter relationship be-
tween lexemes and syntactic roles, which helps language users to recognize thematic roles early
during comprehension.

Abstract

Children learn language from the speech in their home environment. Recent work shows that more infant-directed speech
(IDS) leads to stronger lexical development. But what makes IDS a particularly useful learning signal? Here, we expand on an attention-based account first proposed by Räsänen et al. (2018): that prosodic modifications make IDS less predictable, and thus more interesting. First, we reproduce the critical finding from Räsänen et al.: that lab-recorded IDS pitch is less predictable compared to adult-directed speech (ADS). Next, we show that this result generalizes to the home language environment, finding that IDS in daylong recordings is also less predictable than ADS but that this pattern is much less robust than for IDS recorded in the lab. These results link experimental work on attention and prosodic modifications of IDS to real-world language-learning environments, highlighting some challenges of scaling up analyses of IDS to larger datasets that better capture children’s actual input.

Abstract

Lexical stress is realised similarly in English, German, and
Dutch. On a suprasegmental level, stressed syllables tend to be
longer and more acoustically salient than unstressed syllables;
segmentally, vowels in unstressed syllables are often reduced.
The frequency of unreduced unstressed syllables (where only
the suprasegmental cues indicate lack of stress) however,
differs across the languages. The present studies test whether
listener behaviour is affected by these vocabulary differences,
by investigating German listeners’ use of suprasegmental cues
to lexical stress in German and English word recognition. In a
forced-choice identification task, German listeners correctly
assigned single-syllable fragments (e.g., Kon-) to one of two
words differing in stress (KONto, konZEPT). Thus, German
listeners can exploit suprasegmental information for
identifying words. German listeners also performed above
chance in a similar task in English (with, e.g., DIver, diVERT),
i.e., their sensitivity to these cues also transferred to a nonnative
language. An English listener group, in contrast, failed
in the English fragment task. These findings mirror vocabulary
patterns: German has more words with unreduced unstressed
syllables than English does.

Abstract

Scholars disagree about the extent to which language can tell us
about conceptualisation of the world. Some believe that language
is a direct window onto concepts: Having a word ‘‘bird’’, ‘‘table’’ or
‘‘sour’’ presupposes the corresponding underlying concept, BIRD,
TABLE, SOUR. Others disagree. Words are thought to be uninformative,
or worse, misleading about our underlying conceptual representations;
after all, our mental worlds are full of ideas that we
struggle to express in language. How could this be so, argue sceptics,
if language were a direct window on our inner life? In this presentation,
I consider what language can tell us about the
conceptualisation of taste. By considering linguistic data from
twenty unrelated cultures – varying in subsistence mode (huntergatherer
to industrial), ecological zone (rainforest jungle to desert),
dwelling type (rural and urban), and so forth – I argue any single language is, indeed, impoverished about what it can reveal about
taste. But recurrent lexicalisation patterns across languages can
provide valuable insights about human taste experience. Moreover,
language patterning is part of the data that a good theory of taste
perception has to be answerable for. Taste researchers, therefore,
cannot ignore the crosslinguistic facts.

Abstract

This Research Topic explores the question: what is the relationship between representations of time and space in cultures around the world? This question touches on the broader issue of how humans come to represent and reason about abstract entities – things we cannot see or touch. Time is a particularly opportune domain to investigate this topic. Across cultures, people use spatial representations for time, for example in graphs, time-lines, clocks, sundials, hourglasses, and calendars. In language, time is also heavily related to space, with spatial terms often used to describe the order and duration of events. In English, for example, we might move a meeting forward, push a deadline back, attend a long concert or go on a short break. People also make consistent spatial gestures when talking about time, and appear to spontaneously invoke spatial representations when processing temporal language. A large body of evidence suggests a close correspondence between temporal and spatial language and thought. However, the ways that people spatialize time can differ dramatically across languages and cultures. This research topic identifies and explores some of the sources of this variation, including patterns in spatial thinking, patterns in metaphor, gesture and other cultural systems. This Research Topic explores how speakers of different languages talk about time and space and how they think about these domains, outside of language. The Research Topic invites papers exploring the following issues: 1. Do the linguistic representations of space and time share the same lexical and morphosyntactic resources? 2. To what extent does the conceptualization of time follow the conceptualization of space?

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

This paper presents an analysis of semantic association norms for German nouns. In contrast to prior studies, we not only collected associations elicited by written representations of target objects but also by their pictorial representations. In a first analysis, we identified systematic differences in the type and distribution of associate responses for the two presentation forms. In a second analysis, we applied a soft cluster analysis to the collected target-response pairs. We subsequently used the clustering to predict noun ambiguity and to discriminate senses in our target nouns.

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

Our knowledge of speech perception is largely based on experiments conducted with carefully recorded clear speech presented under good listening conditions to undistracted listeners - a near-ideal situation, in other words. But the reality poses a set of different challenges. First of all, listeners may need to divide their attention between speech comprehension and another task (e.g., driving). Outside the laboratory, the speech signal is often slurred by less than careful pronunciation and the listener has to deal with background noise. Moreover, in a globalized world, listeners need to understand speech in more than their native language. Relatedly, the speakers we listen to often have a different language background so we have to deal with a foreign or regional accent we are not familiar with. Finally, outside the laboratory, speech perception is not an end in itself, but rather a mean to contribute to a conversation. Listeners do not only need to understand the speech they are hearing, they also need to use this information to plan and time their own responses. For this special topic, we invite papers that address any of these ecological aspects of speech perception.

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

Studies have shown that listeners segmenting unfamiliar languages transfer native-language (L1) segmentation cues. These studies, however, conflated L1 and recent linguistic exposure. The present study investigates the relative influences of L1 and recent linguistic exposure on the use of prosodic cues for segmenting an artificial language (AL). Participants were L1-French listeners, high-proficiency L2-French L1-English listeners, and L1-English listeners without functional knowledge of French. The prosodic cue assessed was F0 rise, which is word-final in French, but in English tends to be word-initial. 30 participants heard a 20-minute AL speech stream with word-final boundaries marked by F0 rise, and decided in a subsequent listening task which of two words (without word-final F0 rise) had been heard in the speech stream. The analyses revealed a marginally significant effect of L1 (all listeners) and, importantly, a significant effect of recent linguistic exposure (L1-French and L2-French listeners): accuracy increased with decreasing time in the US since the listeners’ last significant (3+ months) stay in a French-speaking environment. Interestingly, no effect of L2 proficiency was found (L2-French listeners).

Abstract

Language resources can be divided into structural resources treating phonology, morphosyntax, semantics etc. and resources treating the social, demographic, ethnic, political context. A third type are meta-resources, like bibliographies, which provide access to the resources of the first two kinds. This poster will present the Glottolog/Langdoc project, a comprehensive bibliography providing web access to 180k bibliographical records to (mainly) low visibility resources from low-density languages. The resources are annotated for macro-area, content language, and document type and are available in XHTML and RDF.

Abstract

In this paper we try to contribute to the body of knowledge about the acquisition of English epistemic modal verbs (e.g. Mary may/has to be at school). Semantically, these verbs encode possibility or necessity with respect to available evidence. Pragmatically, the use of epistemic modals often gives rise to scalar conversational inferences (Mary may be at school -> Mary doesn’t have to be at school). The acquisition of epistemic modals is challenging for children on both these levels. In this paper, we present findings from two studies which were conducted with 5-year-old children and adults. Our findings, unlike previous work, show that 5-yr-olds have mastered epistemic modal semantics, including the notions of necessity and possibility. However, they are still in the process of acquiring epistemic modal pragmatics.

Abstract

Automating robot behavior in a specific situation is an active area of research. There are several approaches available in the literature of robotics to cater for the automatic behavior of a robot. However, when it comes to humanoids or human-robot interaction in general, the area has been less explored. In this paper, a pseudo-randomization approach has been introduced to automatize the gestures and facial expressions of an interactive humanoid robot called ROBIN based on its mental state. A significant number of gestures and facial expressions have been implemented to allow the robot more options to perform a relevant action or reaction based on visual stimuli. There is a display of noticeable differences in the behaviour of the robot for the same stimuli perceived from an interaction partner. This slight autonomous behavioural change in the robot clearly shows a notion of automation in behaviour. The results from experimental scenarios and human-centered evaluation of the system help validate the approach.

Abstract

En este artículo se desarrolla un método automático de segmentación de fonemas no supervisado. Este método utiliza el algoritmo de agrupación de máximo margen [1] para realizar segmentación de fonemas sobre habla continua sin necesidad de información a priori para el entrenamiento del sistema.

Abstract

This study investigates whether the acoustic durations of derivational affixes in Dutch are affected by the frequency of the word they occur in. In a word naming experiment, subjects were presented with a large number of words containing one of the affixes ge-, ver-, ont, or -lijk. Their responses were recorded on DAT tapes, and the durations of the affixes were measured using Automatic Speech Recognition technology. To investigate whether frequency also affected durations when speech rate was high, the presentation rate of the stimuli was varied. The results show that a higher frequency of the word as a whole led to shorter acoustic realizations for all affixes. Furthermore, affixes became shorter as the presentation rate of the stimuli increased. There was no interaction between word frequency and presentation rate, suggesting that the frequency effect also applies in situations in which the speed of articulation is very high.

Abstract

Two eye-tracking experiments tested whether native listeners can adapt
to reductions in casual Dutch speech. Listeners were exposed to segmental
([b] > [m]), syllabic (full-vowel-deletion), or no reductions. In a subsequent
test phase, all three listener groups were tested on how efficiently they could
recognize both types of reduced words. In the first Experiment’s exposure
phase, the (un)reduced target words were predictable. The segmental reductions
were completely consistent (i.e., involved the same input sequences).
Learning about them was found to be pattern-specific and generalized in the
test phase to new reduced /b/-words. The syllabic reductions were not consistent
(i.e., involved variable input sequences). Learning about them was
weak and not pattern-specific. Experiment 2 examined effects of word repetition
and predictability. The (un-)reduced test words appeared in the exposure
phase and were not predictable. There was no evidence of learning for
the segmental reductions, probably because they were not predictable during
exposure. But there was word-specific learning for the vowel-deleted words.
The results suggest that learning about reductions is pattern-specific and
generalizes to new words if the input is consistent and predictable. With
variable input, there is more likely to be adaptation to a general speaking
style and word-specific learning.

Abstract

Cognitive research is often focused on experimental condition-driven reactions. Ethological studies frequently
rely on the observation of naturally occurring specific behaviors. In both cases, subjects are filmed during the
study, so that afterwards behaviors can be coded on video. Coding should typically be blind to experimental
conditions, but often requires more information than that present on video. We introduce a method for blindcoding
of behavioral videos that takes care of both issues via three main innovations. First, of particular
significance for playback studies, it allows creation of a “soundtrack” of the study, that is, a track composed of
synthesized sounds representing different aspects of the experimental conditions, or other events, over time.
Second, it facilitates coding behavior using this audio track, together with the possibly muted original video.
This enables coding blindly to conditions as required, but not ignoring other relevant events. Third, our method
makes use of freely available, multi-platform software, including scripts we developed.

Abstract

The ultimate goal of our research is to develop a computational model of human speech recognition that is able to capture the effects of fine-grained acoustic variation on speech recognition behaviour. As part of this work we are investigating automatic feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. In the experiments reported here, we compared support vector machines (SVMs) with multilayer perceptrons (MLPs). MLPs have been widely (and rather successfully) used for the task of multi-value articulatory feature classification, while (to the best of our knowledge) SVMs have not. This paper compares the performances of the two classifiers and analyses the results in order to better understand the articulatory representations. It was found that the MLPs outperformed the SVMs, but it is concluded that both classifiers exhibit similar behaviour in terms of patterns of errors.

Abstract

In foreign-accented speech, pronunciation typically deviates from the canonical form to some degree. For native listeners, it has been shown that word recognition is more difficult for strongly-accented words than for less strongly-accented words. Furthermore recognition of strongly-accented words becomes easier with additional exposure to the foreign accent. In this paper, listeners’ behaviour was simulated with Fine-tracker, a computational model of word recognition that uses real speech as input. The simulations showed that, in line with human listeners, 1) Fine-Tracker’s recognition outcome is modulated by the degree of accentedness and 2) it improves slightly after brief exposure with the accent. On the level of individual words, however, Fine-tracker failed to correctly simulate listeners’ behaviour, possibly due to differences in overall familiarity with the chosen accent (German-accented Dutch) between human listeners and Fine-Tracker.

Abstract

Aging often affects sensitivity to the higher frequencies, which results in the loss of sensitivity to phonetic detail in speech. Hearing loss may therefore interfere with the categorisation of two consonants that have most information to differentiate between them in those higher frequencies and less in the lower frequencies, e.g., /f/ and /s/. We investigate two acoustic cues, i.e., formant transitions and fricative intensity, that older listeners might use to differentiate between /f/ and /s/. The results of two phonetic categorisation tasks on 38 older listeners (aged 60+) with varying degrees of hearing loss indicate that older listeners seem to use formant transitions as a cue to distinguish /s/ from /f/. Moreover, this ability is not impacted by hearing loss. On the other hand, listeners with increased hearing loss seem to rely more on intensity for fricative identification. Thus, progressive hearing loss may lead to gradual changes in perceptual cue weighting.

Abstract

Young listeners can quickly modify their interpretation of a speech sound when a talker produces the sound ambiguously. Young Dutch listeners rely mainly on the higher frequencies to distinguish between /f/ and /s/, but these higher frequencies are particularly vulnerable to age-related hearing loss. We therefore tested whether older Dutch listeners can show perceptual retuning given an ambiguous pronunciation in between /f/ and /s/. Results of a lexically-guided perceptual learning experiment showed that older Dutch listeners are still able to learn non-standard pronunciations of /f/ and /s/. Possibly, the older listeners have learned to rely on other acoustic cues, such as formant transitions, to distinguish between /f/ and /s/. However, the size and duration of the perceptual effect is influenced by hearing loss, with listeners with poorer hearing showing a smaller and a shorter-lived learning effect.

Abstract

This presentation will address aspects of the expression of emotion in non-verbal vocal behaviour, specifically attempting to determine the roles of both positive and negative emotions, their acoustic bases, and the extent to which these are recognized in non-Western cultures.

Abstract

Due to its numerous bibliometric entries of scholarly articles and connected information Wikidata can serve as an open and rich
source for deep scientometrical analyses. However, there are currently certain limitations: While 31.5% of all Wikidata entries represent scientific articles, only 8.9% are entries describing a person and the number
of entries researcher is accordingly even lower. Another issue is the frequent absence of established relations between the scholarly article item and the author item although the author is already listed in Wikidata.
To fill this gap and to improve the content of Wikidata in general, we established a workflow for matching authors and scholarly publications by integrating data from the ORCID (Open Researcher and Contributor ID) database. By this approach we were able to extend Wikidata by more than 12k author-publication relations and the method can be
transferred to other enrichments based on ORCID data. This is extension is beneficial for Wikidata users performing bibliometrical analyses or using such metadata for other purposes.

Abstract

Previous fNIRS studies have suggested that adult-child cooperation is accompanied by increased inter-brain synchrony. However, its reflection in the electrophysiological synchrony remains unclear. In this study, we designed a naturalistic and well-controlled adult-child interaction paradigm using a tangram solving video game, and recorded dual-EEG from child and adult dyads during cooperative and individual conditions. By calculating the directed inter-brain connectivity in the theta and alpha bands, we found that the inter-brain frontal network was more densely connected and stronger in strength during the cooperative than the individual condition when the adult was watching the child playing. Moreover, the inter-brain network across different dyads shared more common information flows from the player to the observer during cooperation, but was more individually different in solo play. The results suggest an enhancement in inter-brain EEG interactions during adult-child cooperation. However, the enhancement was evident in all cooperative cases but partly depended on the role of participants.

Abstract

When perceiving vowels, listeners adjust to speaker-specific vocal-tract characteristics (such as F1) through "extrinsic vowel normalization". This effect is observed as a shift in the location of categorization boundaries of vowel continua. Similar effects have been found with non-speech. Non-speech materials, however, have consistently led to smaller effect-sizes, perhaps because of a lack of attention to non-speech. The present study investigated this possibility. Non-speech materials that had previously been shown to elicit reduced normalization effects were tested again, with the addition of an attention manipulation. The results show that increased attention does not lead to increased normalization effects, suggesting that vowel normalization is mainly determined by bottom-up signal characteristics.

Abstract

ELAN is a versatile multimedia annotation tool that is being developed at the Max Planck Institute for Psycholinguistics. About a decade ago it emerged out of a number of corpus tools and utilities and it has been extended ever since. This paper focuses on the efforts made to ensure that the application keeps up with the growing needs of that era in linguistics and multimodality research; growing needs in terms of length and resolution of recordings, the number of recordings made and transcribed and the number of levels of annotation per transcription.

Abstract

Within scientific institutes there exist many language resources. These resources are often quite specialized and relatively unknown. The current infrastructural initiatives try to tackle this issue by collecting metadata about the resources and establishing centers with stable repositories to ensure the availability of the resources. It would be beneficial if the researcher could, by means of a simple query, determine which resources and which centers contain information useful to his or her research, or even work on a set of distributed resources as a virtual corpus. In this article we propose an architecture for a distributed search environment allowing researchers to perform searches in a set of distributed language resources.

Abstract

This paper describes ongoing research aiming at the description of variation in speech as represented by asynchronous articulatory features. We will first illustrate how distances in the articulatory feature space can be used for event detection along speech trajectories in this space. The temporal structure imposed by the cosine distance in articulatory feature space coincides to a large extent with the manual segmentation on phone level. The analysis also indicates that the articulatory feature representation provides better such alignments than the MFCC representation does. Secondly, we will present first results that indicate that articulatory features can be used to probe for acoustic differences in the onsets of Dutch singulars and plurals.

Abstract

This paper builds on previous work that aims at unraveling the structure of the speech signal by means of using probabilistic representations. The context of this work is a multi-pass speech recognition system in which a phone lattice is created and used as a basis for a lexical search in which symbolic mismatches are allowed at certain costs. The focus is on the optimization of the costs of phone insertions, deletions and substitutions that are used in the lexical decoding pass. Two optimization approaches are presented, one related to a multi-pass computational model for human speech recognition, the other based on a decoding in which Bayes’ risks are minimized. In the final section, the advantages of these optimization methods are discussed and compared.

Abstract

Classical phonetic studies have shown that acoustic-articulatory cues can be interchanged without affecting the resulting phoneme percept (‘cue trading’). Cue trading has so far mainly been investigated in the context of phoneme identification. In this study, we investigate cue trading in word recognition, because words are the units of speech through which we communicate. This paper aims to provide a method to quantify cue trading effects by using a computational model of human word recognition. This model takes the acoustic signal as input and represents speech using articulatory feature streams. Importantly, it allows cue trading and underspecification. Its set-up is inspired by the functionality of Fine-Tracker, a recent computational model of human word recognition. This approach makes it possible, for the first time, to quantify cue trading in terms of a trade-off between features and to investigate cue trading in the context of a word recognition task.

Abstract

In face-to-face conversation, recipients might use the bodily movements of the speaker (e.g. gestures) to facilitate language processing. It has been suggested that one way through which this facilitation may happen is prediction. However, for this to be possible, gestures would need to precede speech, and it is unclear whether this is true during natural conversation.
In a corpus of Dutch conversations, we annotated hand gestures that represent semantic information and occurred during questions, and the word(s) which corresponded most closely to the gesturally depicted meaning. Thus, we tested whether representational gestures temporally precede their lexical affiliates. Further, to see whether preceding gestures may indeed facilitate language processing, we asked whether the gesture-speech asynchrony predicts the response time to the question the gesture is part of.
Gestures and their strokes (most meaningful movement component) indeed preceded the corresponding lexical information, thus demonstrating their predictive potential. However, while questions with gestures got faster responses than questions without, there was no evidence that questions with larger gesture-speech asynchronies get faster responses. These results suggest that gestures indeed have the potential to facilitate predictive language processing, but further analyses on larger datasets are needed to test for links between asynchrony and processing advantages.

Abstract

Multilingual speakers are able to switch from
one language to the other (“code-switch”) be-
tween or within sentences. Because the under-
lying cognitive mechanisms are not well un-
derstood, in this study we use computational
cognitive modeling to shed light on the pro-
cess of code-switching. We employed the
Bilingual Dual-path model, a Recurrent Neu-
ral Network of bilingual sentence production
(Tsoukala et al., 2017) and simulated sentence
production in simultaneous Spanish-English
bilinguals. Our first goal was to investigate
whether the model would code-switch with-
out being exposed to code-switched training
input. The model indeed produced code-
switches even without any exposure to such
input and the patterns of code-switches are
in line with earlier linguistic work (Poplack,
1980). The second goal of this study was to
investigate an auxiliary phrase asymmetry that
exists in Spanish-English code-switched pro-
duction. Using this cognitive model, we ex-
amined a possible cause for this asymmetry.
To our knowledge, this is the first computa-
tional cognitive model that aims to simulate
code-switched sentence production.

Abstract

This paper represents a pilot investigation of primed accentuation patterns produced by advanced Dutch speakers of Italian as a second language (L2). Contrastive accent patterns within prepositional phrases were elicited in a semispontaneous dialogue entertained with a confederate native speaker of Italian. The aim of the analysis was to compare learner’s contrastive accentual configurations induced by the confederate speaker’s prime against those produced by Italian and Dutch natives in the same testing conditions. F0 and speech rate data were analysed by applying powerful datadriven techniques available in the Functional Data Analysis statistical framework. Results reveal different accentual configurations in L1 and L2 Italian in response to the confederate’s prime. We conclude that learner’s accentual patterns mirror those ones produced by their L1 control group (prosodic-transfer hypothesis) although the hypothesis of a transient priming effect on learners’ choice of contrastive patterns cannot be completely ruled out.

Abstract

This paper introduces a new CLARIN Knowledge Center which is the K-Centre for Atypical Communication Expertise (ACE for short) which has been established at the Centre for Language and Speech Technology (CLST) at Radboud University. Atypical communication is an umbrella term used here to denote language use by second language learners, people with language disorders or those suffering from language disabilities, but also more broadly by bilinguals and users of sign languages. It involves multiple modalities (text, speech, sign, gesture) and encompasses different developmental stages. ACE closely collaborates with The Language Archive (TLA) at the Max Planck Institute for Psycholinguistics in order to safeguard GDPR-compliant data storage and access. We explain the mission of ACE and show its potential on a number of showcases and a use case.

Abstract

A series of experiments is conducted on naïve native speakers of Dutch and English to study the scope relation between tense and epistemic modality. The results are consistent with the claim that epistemics scope over tense (Stowell 2004, Hacquard 2006, a.o.), and challenge recent research that states that epistemics can, or must, scope under tense (von Fintel and Gillies 2007, Rullmann & Matthewson 2018): Dutch and English participants in a Truth Value Judgment Task judge sentences to be false when the past tense forms of the modals have to and moeten 'have to' are used to make an epistemic claim that held at a time before speech time, and true when they are used to make an epistemic claim that holds at speech time. Moreover, English participants in an Acceptability Judgment Task judge sentences to be infelicitous when the same past tense form of have to is used to make an epistemic claim that held at a time before speech time. Besides these general patterns, the results show variation within and across the two languages, which leads to interesting new questions about the interaction between tense and (epistemic) modality.

Abstract

How can people communicate successfully while keeping resource costs low in the face of ambiguity? We present a principled theoretical analysis comparing two strategies for disambiguation in communication: (i) pragmatic reasoning, where communicators reason about each other, and (ii) other-initiated repair, where communicators signal and resolve trouble interactively. Using agent-based simulations and computational complexity analyses, we compare the efficiency of these strategies in terms of communicative success, computation cost and interaction cost. We show that agents with a simple repair mechanism can increase efficiency, compared to pragmatic agents, by reducing their computational burden at the cost of longer interactions. We also find that efficiency is highly contingent on the mechanism, highlighting the importance of explicit formalisation and computational rigour.

Abstract

In this paper we present the Virtual Language Observatory (VLO), a metadata-based portal for language resources. It is completely based on the Component Metadata (CMDI) and ISOcat standards. This approach allows for the use of heterogeneous metadata schemas while maintaining the semantic compatibility. We describe the metadata harvesting process, based on OAI-PMH, and the conversion from several formats (OLAC, IMDI and the CLARIN LRT inventory) to their CMDI counterpart profiles. Then we focus on some post-processing steps to polish the harvested records. Next, the ingestion of the CMDI files into the VLO facet browser is described. We also include an overview of the changes since the first version of the VLO, based on user feedback from the CLARIN community. Finally there is an overview of additional ideas and improvements for future versions of the VLO.

Abstract

This paper presents a corpus study that investigates the co-occurrence of reduced word forms in natural speech. We extracted Dutch past participles from three different speech registers and investigated the influence of several predictor variables on the presence and duration of schwas in prefixes and /t/s in suffixes. Our results suggest that reduced word forms tend to co-occur even if we partial out the effect of speech rate. The implications of our findings for episodic and abstractionist models of lexical representation are discussed.

Abstract

Information in speech does not unfold discretely over time; perceptual cues are gradient and overlapped. However, this varies greatly across segments and environments: listeners cannot identify the affricate in /ptS/ until the frication, but information about the vowel in /li/ begins early. Unlike most prior studies, which have concentrated on subsets of language sounds, this study tests perception of every English segment in every phonetic environment, sampling perceptual identification at six points in time (13,470 stimuli/listener; 20 listeners). Results show that information about consonants after another segment is most localized for affricates (almost entirely in the release), and most gradual for voiced stops. In comparison to stressed vowels, unstressed vowels have less information spreading to
neighboring segments and are less well identified. Indeed, many vowels,
especially lax ones, are poorly identified even by the end of the following segment. This may partly reflect listeners’ familiarity with English vowels’ dialectal variability. Diphthongs and diphthongal tense vowels show the most sudden improvement in identification, similar to affricates among the consonants, suggesting that information about segments defined by acoustic change is highly localized. This large dataset provides insights into speech perception and data for probabilistic modeling of spoken word recognition.

Abstract

Recent studies using phoneme detection tasks have shown that spoken-language processing is neither facilitated nor interfered with by optional assimilation, but is inhibited by violation of obligatory assimilation. Interpretation of these results depends on an assessment of their generality, specifically, whether they also obtain when listeners are processing nonnative language. Two separate experiments are presented in which native listeners of German and native listeners of Dutch had to detect a target fricative in legal monosyllabic Dutch nonwords. All of the nonwords were correct realisations in standard Dutch. For German listeners, however, half of the nonwords contained phoneme strings which violate the German fricative assimilation rule. Whereas the Dutch listeners showed no significant effects, German listeners detected the target fricative faster when the German fricative assimilation was violated than when no violation occurred. The results might suggest that violation of assimilation rules does not have to make processing more difficult per se.

Abstract

In the CLARIN infrastructure various national projects have started initiatives to allow users of the infrastructure to create chains or workflows of web services. The Component Metadata (CMD) core model for web services described in this paper tries to align the metadata descriptions of these various initiatives. This should allow chaining/workflow engines to find matching and invoke services. The paper describes the landscape of web services architectures and the state of the national initiatives. Based on this a CMD core model for CLARIN is proposed, which, within some limits, can be adapted to the specific needs of an initiative by the standard facilities of CMD. The paper closes with the current state and usage of the model and a look into the future.

Abstract

The ISOcat Data Category Registry contains basically a flat and easily extensible list of data category specifications. To foster reuse and standardization only very shallow relationships among data categories are stored in the registry. However, to assist crosswalks, possibly based on personal views, between various (application) domains and to overcome possible proliferation of data categories more types of ontological relationships need to be specified. RELcat is a first prototype of a Relation Registry, which allows storing arbitrary relationships. These relationships can reflect the personal view of one linguist or a larger community. The basis of the registry is a relation type taxonomy that can easily be extended. This allows on one hand to load existing sets of relations specified in, for example, an OWL (2) ontology or SKOS taxonomy. And on the other hand allows algorithms that query the registry to traverse the stored semantic network to remain ignorant of the original source vocabulary. This paper describes first experiences with RELcat and explains some initial design decisions.

Abstract

Automatic Language Identification of written texts is a well-established area of research in Computational Linguistics. State-of-the-art algorithms often rely on n-gram character models to identify the correct language of texts, with good results seen for European languages. In this paper we propose the use of a character n-gram model and a word n-gram language model for the automatic classification of two written varieties of Portuguese: European and Brazilian. Results reached 0.998 for accuracy using character 4-grams.

Abstract

Arbil is an application designed to create and manage metadata for research data and to arrange this data into a structure appropriate for archiving. The metadata is displayed in tables, which allows an overview of the metadata and the ability to populate and update many metadata sections in bulk. Both IMDI and Clarin metadata formats are supported and Arbil has been designed as a local application so that it can also be used offline, for instance in remote field sites. The metadata can be entered in any order or at any stage that the user is able; once the metadata and its data are ready for archiving and an Internet connection is available it can be exported from Arbil and in the case of IMDI it can then be transferred to the main archive via LAMUS (archive management and upload system).

Abstract

Introduction Speech research saw a dramatic change in paradigm in the 90-ies. While earlier the discussion was dominated by a phoneticians’ approach who knew about phenomena in the speech signal, the situation completely changed after stochastic machinery such as Hidden Markov Models [1] and Artificial Neural Networks [2] had been introduced. Speech processing was now dominated by a purely mathematic approach that basically ignored all existing knowledge about the speech production process and the perception mechanisms. The key was now to construct a large enough training set that would allow identifying the many free parameters of such stochastic engines. In case that the training set is representative and the annotations of the training sets are widely ‘correct’ we could assume to get a satisfyingly functioning recognizer. While the success of knowledge-based systems such as Hearsay II [3] was limited, the statistically based approach led to great improvements in recognition rates and to industrial applications.

Abstract

Utilization of computer tools in linguistic research has gained importance with the maturation of media frameworks for the handling of digital audio and video. The increased use of these tools in gesture, sign language and multimodal interaction studies has led to stronger requirements on the flexibility, the efficiency and in particular the time accuracy of annotation tools. This paper describes the efforts made to make ELAN a tool that meets these requirements, with special attention to the developments in the area of time accuracy. In subsequent sections an overview will be given of other enhancements in the latest versions of ELAN, that make it a useful tool in multimodality research.

Abstract

A number of serious reasons will convince an increasing amount of researchers to store their relevant material in centers which we will call "language resource archives". They combine the duty of taking care of long-term preservation as well as the task to give access to their material to different user groups. Access here is meant in the sense that an active interaction with the data will be made possible to support the integration of new data, new versions or commentaries of all sort. Modern Language Resource Archives will have to adhere to a number of basic principles to fulfill all requirements and they will have to be involved in federations to create joint language resource domains making it even more simple for the researchers to access the data. This paper makes an attempt to formulate the essential pillars language resource archives have to adhere to.

Abstract

According to a widely-held view among various scholars, olfaction is inferior to other human senses. It is also believed by many that languages do not have words for describing smells. Data collected among the Maniq, a small population of nomadic foragers in southern Thailand, challenge the above claims and point to a great linguistic and cultural elaboration of odor. This article presents evidence of the importance of olfaction in indigenous rituals and beliefs, as well as in the lexicon. The results demonstrate the richness and complexity of the domain of smell in Maniq society and thereby challenge the universal paucity of olfactory terms and insignificance of olfaction for humans.

Abstract

Language users process utterances by segmenting them into many cognitive units, which vary in their sizes and linguistic levels. Although we can do such unitization/segmentation easily, its cognitive mechanism is still not clear. This paper proposes an unsupervised model, Less-is-Better (LiB), to simulate the human cognitive process with respect to language unitization/segmentation. LiB follows the principle of least effort and aims to build a lexicon which minimizes the number of unit tokens (alleviating the effort of analysis) and number of unit types (alleviating the effort of storage) at the same time on any given corpus. LiB’s workflow is inspired by empirical cognitive phenomena. The design makes the mechanism of LiB cognitively plausible and the computational requirement light-weight. The lexicon generated by LiB performs the best among different types of lexicons (e.g. ground-truth words) both from an information-theoretical view and a cognitive view, which suggests that the LiB lexicon may be a plausible proxy of the mental lexicon.

Abstract

Automatic Language Identification of written texts is a well-established area of research in Computational Linguistics. State-of-the-art algorithms often rely on n-gram character models to identify the correct language of texts, with good results seen for European languages. In this paper we propose the use of a character n-gram model and a word n-gram language model for the automatic classification of two written varieties of Portuguese: European and Brazilian. Results reached 0.998 for accuracy using character 4-grams.

Abstract

This study presents a new language identification model for pluricentric languages that uses n-gram language models at the character and word level. The model is evaluated in two steps. The first step consists of the identification of two varieties of Spanish (Argentina and Spain) and two varieties of French (Quebec and France) evaluated independently in binary classification schemes. The second step integrates these language models in a six-class classification with two Portuguese varieties.

Abstract

Language is multimodal: non-linguistic cues, such as prosody,
gestures and mouth movements, are always present in face-to-
face communication and interact to support processing. In this
paper, we ask whether and how multimodal cues affect L2
processing by recording EEG for highly proficient bilinguals
when watching naturalistic materials. For each word, we
quantified surprisal and the informativeness of prosody,
gestures, and mouth movements. We found that each cue
modulates the N400: prosodic accentuation, meaningful
gestures, and informative mouth movements all reduce N400.
Further, effects of meaningful gestures but not mouth
informativeness are enhanced by prosodic accentuation,
whereas effects of mouth are enhanced by meaningful gestures
but reduced by beat gestures. Compared with L1, L2
participants benefit less from cues and their interactions, except
for meaningful gestures and mouth movements. Thus, in real-
world language comprehension, L2 comprehenders use
multimodal cues just as L1 speakers albeit to a lesser extent.

Abstract

Learning verbs is challenging because it is difficult to infer the precise meaning of a verb when there are a multitude of relations that one can derive from a single event. To study this verb learning challenge, we used children's egocentric view collected from naturalistic toy-play interaction as learning materials and investigated how visual and linguistic information provided in individual naming moments as well as cross-situational information provided from multiple learning moments can help learners resolve this mapping problem using the Human Simulation Paradigm. Our results show that learners benefit from seeing children's egocentric views compared to third-person observations. In addition, linguistic information can help learners identify the correct verb meaning by eliminating possible meanings that do not belong to the linguistic category. Learners are also able to integrate visual and linguistic information both within and across learning situations to reduce the ambiguity in the space of possible verb meanings.

Abstract

To acquire the meaning of a verb, language learners not only need to find the correct mapping between a specific verb and an action or event in the world, but also infer the underlying relational meaning that the verb encodes. Most verb naming instances in naturalistic contexts are highly ambiguous as many possible actions can be embedded in the same scenario and many possible verbs can be used to describe those actions. To understand whether learners can find the correct verb meaning from referentially ambiguous learning situations, we conducted three experiments using the Human Simulation Paradigm with adult learners. Our results suggest that although finding the right verb meaning from one learning instance is hard, there is a statistical solution to this problem. When provided with multiple verb learning instances all referring to the same verb, learners are able to aggregate information across situations and gradually converge to the correct semantic space. Even in cases where they may not guess the exact target verb, they can still discover the right meaning by guessing a similar verb that is semantically close to the ground truth.

Abstract

This study investigates the difficulty of people with Mild Cognitive Impairment (MCI), mild and moderate Alzheimer’s disease (AD) in the production and comprehension of psychological verbs, as thematic realization may involve both the canonical and non-canonical realization of arguments. More specifically, we aim to examine whether there is a deficit in the mapping of syntactic and semantic representations in psych-predicates regarding Greek-speaking individuals with MCI and AD, and whether the linguistic abilities associated with θ-role assignment decrease as the disease progresses. Moreover, given the decline of cognitive abilities in people with MCI and AD, we explore the effects of components of memory (Semantic, Episodic, and Working Memory) on the assignment of thematic roles in constructions with psychological verbs.