Publications

Abstract

When we communicate with others, we often repeat aspects of each other's communicative behavior such as sentence structures and words. Such behavioral alignment has been mostly studied for speech or text. Yet, language use is mostly multimodal, flexibly using speech and gestures to convey messages. Here, we explore the use of alignment in speech (words) and co-speech gestures (iconic gestures) in a referential communication task aimed at finding labels for novel objects in interaction. In particular, we investigate how people flexibly use lexical and gestural alignment to create shared labels for novel objects and whether alignment in speech and gesture are related over time. The present study shows that interlocutors establish shared labels multimodally, and alignment in words and iconic gestures are used throughout the interaction. We also show that the amount of lexical alignment positively associates with the amount of gestural alignment over time, suggesting a close relationship between alignment in the vocal and manual modalities.

Abstract

Proficient readers typically fixate near the center of a word, with a slight bias towards word onset. We explore a novel account of this phenomenon based on combining information-theory with visual perceptual constraints in a connectionist model of visual word recognition. This account posits that the amount of information-content available for word identification varies across fixation locations and across languages, thereby explaining the overall fixation location bias in different languages, making the novel prediction that certain words are more readily identified when fixating at an atypical fixation location, and predicting specific cross-linguistic differences. We tested these predictions across several simulations in English and Hebrew, and in a pilot behavioral experiment. Results confirmed that the bias to fixate closer to word onset aligns with maximizing information in the visual signal, that some words are more readily identified at atypical fixation locations, and that these effects vary to some degree across languages.

Abstract

The RELISH project promotes language-oriented research by addressing a two-pronged problem: (1) the lack of harmonization between digital standards for lexical information in Europe and America, and (2) the lack of interoperability among existing lexicons of endangered languages, in particular those created with the Shoebox/Toolbox lexicon building software. The cooperation partners in the RELISH project are the University of Frankfurt (FRA), the Max Planck Institute for Psycholinguistics (MPI Nijmegen), and Eastern Michigan University, the host of the Linguist List (ILIT). The project aims at harmonizing key European and American digital standards whose divergence has hitherto impeded international collaboration on language technology for resource creation and analysis, as well as web services for archive access. Focusing on several lexicons of endangered languages, the project will establish a unified way of referencing lexicon structure and linguistic concepts, and develop a procedure for migrating these heterogeneous lexicons to a standards-compliant format. Once developed, the procedure will be generalizable to the large store of lexical resources involved in the LEGO and DoBeS projects.

Abstract

Data augmentation techniques have been widely used in visual recognition tasks as it is easy to generate new
data by simple and straight forward image transformations. However, when it comes to text data augmen-
tations, it is difficult to find appropriate transformation techniques which also preserve the contextual and
grammatical structure of language texts. In this paper, we explore various text data augmentation techniques
in text space and word embedding space. We study the effect of various augmented datasets on the efficiency
of different deep learning models for relation classification in text.

Abstract

Analysis of the functions of nominal apposition in a number of Latin authors representing different periods, genres, and
linguistic registers shows (1) that nominal apposition in Latin had a wide variety of functions; (2) that genre had some
effect on functional use; (3) that change did not affect semantic fields as such; and (4) that with time the occurrence of
apposition increasingly came to depend on the semantic field and within the semantic field on the individual lexical items.
The ‘per-word’ treatment –also attested for the structural development of nominal apposition– underscores the specific
characteristics of nominal apposition as a phenomenon at the cross-roads of syntax and derivational morphology

Abstract

Recognizing the limitations of standard vision assessments in capturing the real-world capabilities of individuals with low vision, we investigated the potential of the Seguin Form Board Test (SFBT), a widely-used intelligence assessment employing a visuo-haptic shape-fitting task, as an estimator of vision's practical utility. We present findings from 23 children from India, who underwent treatment for congenital bilateral dense cataracts, and 21 control participants. To assess the development of functional visual ability, we conducted the SFBT and the standard measure of visual acuity, before and longitudinally after treatment. We observed a dissociation in the development of shape-fitting and visual acuity. Improvements of patients' shape-fitting preceded enhancements in their visual acuity after surgery and emerged even with acuity worse than that of control participants. Our findings highlight the importance of incorporating multi-modal and cognitive aspects into evaluations of visual proficiency in low-vision conditions, to better reflect vision's impact on daily activities.

Abstract

The event-related potential (ERP) component named phonological mismatch negativity (PMN) arises when listeners hear an unexpected word form in a spoken sentence [1]. The PMN is thought to reflect the mismatch between expected and perceived auditory speech input. In this paper, we use the PMN to test a central premise in the predictive coding framework [2], namely that the mismatch between prior expectations and sensory input is an important mechanism of perception. We test this with natural speech materials containing approximately 50,000 word tokens. The corresponding EEG-signal was recorded while participants (n = 48) listened to these materials. Following [3], we quantify the mismatch with two word probability distributions (WPD): a WPD based on preceding context, and a WPD that is additionally updated based on the incoming audio of the current word. We use the between-WPD cross entropy for each word in the utterances and show that a higher cross entropy correlates with a more negative PMN. Our results show that listeners anticipate auditory input while processing each word in naturalistic speech. Moreover, complementing previous research, we show that predictive language processing occurs across the whole probability spectrum.

Abstract

The mismatch between top-down predicted and bottom-up perceptual input is an important mechanism of perception according to the predictive coding framework (Friston, [1]). In this paper we develop and validate a new information-theoretic measure that quantifies the mismatch between expected and observed auditory input during speech processing. We argue that such a mismatch measure is useful for the study of speech processing. To compute the mismatch measure, we use naturalistic speech materials containing approximately 50,000 word tokens. For each word token we first estimate the prior word probability distribution with the aid of statistical language modelling, and next use automatic speech recognition to update this word probability distribution based on the unfolding speech signal. We validate the mismatch measure with multiple analyses, and show that the auditory-based update improves the probability of the correct word and lowers the uncertainty of the word probability distribution. Based on these results, we argue that it is possible to explicitly estimate the mismatch between predicted and perceived speech input with the cross entropy between word expectations computed before and after an auditory update.

Abstract

The study of first language acquisition still strongly relies on behavioural methods to measure underlying linguistic abilities. In the present paper, we closely examine and model one such method, the headturn preference procedure (HPP), which is widely used to measure infant speech segmentation and word recognition abilities Our model takes real speech as input, and only uses basic sensory processing and cognitive capabilities to simulate observable behaviour.We show that the familiarity effect found in many HPP experiments can be simulated without using the phonetic and phonological skills necessary for segmenting test sentences into words. The explicit modelling of the process that converts the result of the cognitive processing of the test sentences into observable behaviour uncovered two issues that can lead to null-results in HPP studies. Our simulations show that caution is needed in making inferences about underlying language skills from behaviour in HPP experiments. The simulations also generated questions that must be addressed in future HPP studies.

Abstract

Although the possibility of referring or citing on-line data from publications is seen at least theoretically as an important means to provide immediate testable proof or simple illustration of a line of reasoning, the practice has not been wide-spread yet and no extensive experience has been gained about the possibilities and problems of referring to raw data-sets. This paper makes a case to investigate the possibility and need of persistent data visualization services that facilitate the inspection and evaluation of the cited data.

Abstract

This paper describes the status of the standardization efforts of a Component Metadata approach for describing Language Resources with metadata. Different linguistic and Language & Technology communities as CLARIN, META-SHARE and NaLiDa use this component approach and see its standardization of as a matter for cooperation that has the possibility to create a large interoperable domain of joint metadata. Starting with an overview of the component metadata approach together with the related semantic interoperability tools and services as the ISOcat data category registry and the relation registry we explain the standardization plan and efforts for component metadata within ISO TC37/SC4. Finally, we present information about uptake and plans of the use of component metadata within the three mentioned linguistic and L&T communities.

Abstract

This study investigates the lexical representation of second-language words that contain difficult to distinguish phonemes. Dutch and English listeners' perception of partially onset-overlapping word pairs like DAFFOdil-DEFIcit and minimal pairs like flash-flesh, was assessed with two cross-modal priming experiments, examining two stages of lexical processing: activation of intended and mismatching lexical representations (Exp.1) and competition between those lexical representations (Exp.2). Exp.1 shows that truncated primes like daffo- and defi- activated lexical representations of mismatching words (either deficit or daffodil) more for L2 than L1 listeners. Exp.2 shows that for minimal pairs, matching primes (prime: flash, target: FLASH) facilitated recognition of visual targets for L1 and L2 listeners alike, whereas mismatching primes (flesh, FLASH) inhibited recognition consistently for L1 listeners but only in a minority of cases for L2 listeners; in most cases, for them, primes facilitated recognition of both words equally strongly. Importantly, all listeners experienced a combination of facilitation and inhibition (and all items sometimes caused facilitation and sometimes inhibition). These results suggest that for all participants, some of the minimal pairs were represented with separate, native-like lexical representations, whereas other pairs were stored as homophones. The nature of the L2 lexical representations thus varied strongly even within listeners.

Abstract

Speech input causes listeners to activate multiple
candidate words which then compete with one
another. These include onset competitors, that share a
beginning (bumper, butter), but also, counterintuitively,
rhyme competitors, sharing an ending
(bumper, jumper). In L1, competition is typically
stronger for onset than for rhyme. In L2, onset
competition has been attested but rhyme competition
has heretofore remained largely unexamined. We
assessed L1 (Dutch) and L2 (English) word
recognition by the same late-bilingual individuals. In
each language, eye gaze was recorded as listeners
heard sentences and viewed sets of drawings: three
unrelated, one depicting an onset or rhyme competitor
of a word in the input. Activation patterns revealed
substantial onset competition but no significant
rhyme competition in either L1 or L2. Rhyme
competition may thus be a “luxury” feature of
maximally efficient listening, to be abandoned when
resources are scarcer, as in listening by late
bilinguals, in either language.

Abstract

Conversational turns often proceed with very brief pauses between speakers. In order to maintain “no gap, no overlap” turntaking, we must be able to anticipate when an ongoing utterance will end, tracking the current speaker for upcoming points of potential floor exchange. The precise set of cues that listeners use for turn-end boundary anticipation is not yet established. We used an eyetracking paradigm to measure adults’ and children’s online turn processing as they watched videos of conversations in their native language (English) and a range of other languages they did not speak. Both adults and children anticipated speaker transitions effectively. In addition, we observed evidence of turn-boundary anticipation for questions even in languages that were unknown to participants, suggesting that listeners’ success in turn-end anticipation does not rely solely on lexical information.

Abstract

Spontaneous gestures play an important role in spatial problem solving. We investigated the functional role and underlying mechanism of spontaneous gestures in spatial problem solving. In Experiment 1, 132 participants were required to solve a mental rotation task (see Figure 1) without speaking. Participants gestured more frequently in difficult trials than in easy trials. In Experiment 2, 66 new participants were given two identical sets of mental rotation tasks problems, as the one used in experiment 1. Participants who were encouraged to gesture in the first set of mental rotation task problemssolved more problems correctly than those who were allowed to gesture or those who were prohibited from gesturing both in the first set and in the second set in which all participants were prohibited from gesturing. The gestures produced by the gestureencouraged group and the gesture-allowed group were not qualitatively different. In Experiment 3, 32 new participants were first given a set of mental rotation problems and then a second set of nongesturing paper folding problems. The gesture-encouraged group solved more problems correctly in the first set of mental rotation problems and the second set of non-gesturing paper folding problems. We concluded that gesture improves spatial problem solving. Furthermore, gesture has a lasting beneficial effect even when gesture is not available and the beneficial effect is problem-general.We suggested that gesture enhances spatial problem solving by provide a rich sensori-motor representation of the physical world and pick up information that is less readily available to visuo-spatial processes.

Abstract

The nature of the connection between musical and spatial processing is controversial. While pitch may be described in spatial terms such as “high” or “low”, it is unclear whether pitch and space are associated but separate dimensions or whether they share representational and processing resources. In the present study, we asked participants to judge whether a target vocal note was the same as (or different from) a preceding cue note. Importantly, target trials were presented as video clips where a singer sometimes gestured upward or downward while singing that target note, thus providing an alternative, concurrent source of spatial information. Our results show that pitch discrimination was significantly biased by the spatial movement in gesture. These effects were eliminated by spatial memory load but preserved under verbal memory load conditions. Together, our findings suggest that pitch and space have a shared representation such that the mental representation of pitch is audiospatial in nature.

Abstract

In natural communication, we typically both see and hear our conversation partner. Speech comprehension thus requires the integration of auditory and visual information from the speech signal. This is for instance evidenced by the Manual McGurk effect, where the perception of lexical stress is biased towards the syllable that has a beat gesture aligned to it. However, there is considerable individual variation in how heavily gestural timing is weighed as a cue to stress. To assess within-individualconsistency, this study investigated the test-retest reliability of the Manual McGurk effect. We reran an earlier Manual McGurk experiment with the same participants, over 1.5 years later. At the group level, we successfully replicated the Manual McGurk effect with a similar effect size. However, a correlation of the by-participant effect sizes in the two identical experiments indicated that there was only a weak correlation between both tests, suggesting that the weighing of gestural information in the perception of lexical stress is stable at the group level, but less so in individuals. Findings are discussed in comparison to other measures of audiovisual integration in speech perception. Index Terms: Audiovisual integration, beat gestures, lexical stress, test-retest reliability

Abstract

publication expected April 2012

Abstract

Part of the remarkable efficiency of listening is
accommodation to unfamiliar talkers’ specific
pronunciations by retuning of phonemic intercategory
boundaries. Such retuning occurs in second
(L2) as well as first language (L1); however, recent
research with emigrés revealed successful adaptation
in the environmental L2 but, unprecedentedly, not in
L1 despite continuing L1 use. A possible explanation
involving relative exposure to novel talkers is here
tested in heritage language users with Mandarin as
family L1 and English as environmental language. In
English, exposure to an ambiguous sound in
disambiguating word contexts prompted the expected
adjustment of phonemic boundaries in subsequent
categorisation. However, no adjustment occurred in
Mandarin, again despite regular use. Participants
reported highly asymmetric interlocutor counts in the
two languages. We conclude that successful retuning
ability requires regular exposure to novel talkers in
the language in question, a criterion not met for the
emigrés’ or for these heritage users’ L1.

Abstract

Listeners process spoken language in ways which are adapted to the phonological structure of their native language. As a consequence, non-native speakers do not listen to a language in the same way as native speakers; moreover, listeners may use their native language listening procedures inappropriately with foreign input. With sufficient experience, however, it may be possible to inhibit this latter (counter-productive) behavior.

Abstract

One of a listener's major tasks in understanding continuous speech is segmenting the speech signal into separate words. When listening conditions are difficult, speakers can help listeners by deliberately speaking more clearly. In three experiments, we examined how word boundaries are produced in deliberately clear speech. We found that speakers do indeed attempt to mark word boundaries; moreover, they differentiate between word boundaries in a way which suggests they are sensitive to listener needs. Application of heuristic segmentation strategies makes word boundaries before strong syllables easiest for listeners to perceive; but under difficult listening conditions speakers pay more attention to marking word boundaries before weak syllables, i.e. they mark those boundaries which are otherwise particularly hard to perceive.

Abstract

Word blends combine fragments from two words, either in speech errors or when a new word is created. Previous work has demonstrated that in Japanese, such blends preserve moraic structure; in English they do not. A similar effect of moraic structure is observed in perceptual research on segmentation of continuous speech in Japanese; English listeners, by contrast, exploit stress units in segmentation, suggesting that a general rhythmic constraint may underlie both findings. The present study examined whether mis parallel would also hold for word blends. In spontaneous English polysyllabic blends, the source words were significantly more likely to be split before a strong than before a weak (unstressed) syllable, i.e. to be split at a stress unit boundary. In an experiment in which listeners were asked to identify the source words of blends, significantly more correct detections resulted when splits had been made before strong syllables. Word blending, like speech segmentation, appears to be constrained by language rhythm.

Abstract

In a 50,000-word corpus of spoken British English the occurrence of words embedded within other words is reported. Within-word embedding in this real speech sample is common, and analogous to the extent of embedding observed in the vocabulary. Imposition of a syllable boundary matching constraint reduces but by no means eliminates spurious embedding. Embedded words are most likely to overlap with the beginning of matrix words, and thus may pose serious problems for speech recognisers.

Abstract

People automatically chunk ongoing dynamic events into discrete units. This paper investigates whether linguistic structure is a factor in this process. We test the claim that describing an event with a serial verb construction will influence a speaker’s conceptual event structure. The grammar of Avatime (a Kwa language spoken in Ghana)requires its speakers to describe some, but not all, placement events using a serial verb construction which also encodes the preceding taking event. We tested Avatime and English speakers’ recognition memory for putting and taking events. Avatime speakers were more likely to falsely recognize putting and taking events from episodes associated with takeput serial verb constructions than from episodes associated with other constructions. English speakers showed no difference in false recognitions between episode types. This demonstrates that memory for episodes is related to the type of language used; and, moreover, across languages different conceptual representations are formed for the same physical episode, paralleling habitual linguistic practices

Abstract

Do interlocutors adjust their conversational strategies to the specific contextual demands of a given situation? Prior studies have yielded conflicting results, making it unclear how strategies vary with demands. We combine insights from qualitative and quantitative approaches in a within-participant experimental design involving two different contexts: spontaneously occurring conversations (SOC) and task-oriented conversations (TOC). We systematically assess backchanneling, other-repair and linguistic alignment. We find that SOC exhibit a higher number of backchannels, a reduced and more generic repair format and higher rates of lexical and syntactic alignment. TOC are characterized by a high number of specific repairs and a lower rate of lexical and syntactic alignment. However, when alignment occurs, more linguistic forms are aligned. The findings show that conversational strategies adapt to specific contextual demands.

Abstract

We present a new transcription mode for the annotation tool ELAN. This mode is designed to speed up the process of creating transcriptions of primary linguistic data (video and/or audio recordings of linguistic behaviour). We survey the basic transcription workflow of some commonly used tools (Transcriber, BlitzScribe, and ELAN) and describe how the new transcription interface improves on these existing implementations. We describe the design of the transcription interface and explore some further possibilities for improvement in the areas of segmentation and computational enrichment of annotations.

Abstract

The widespread occurrence of ideophones, large classes of words specialized in evoking sensory imagery, is little known outside linguistics and anthropology. Ideophones are a common feature in many of the world’s languages but are underdeveloped in English and other Indo-European languages. Here we study the meanings of ideophones in Siwu (a Kwa language from Ghana) using a pile-sorting task. The goal was to uncover the underlying structure of the lexical space and to examine the claimed link between ideophones and perception. We found that Siwu ideophones are principally organized around fine-grained aspects of sensory perception, and map onto salient psychophysical dimensions identified in sensory science. The results ratify ideophones as dedicated sensory vocabulary and underline the relevance of ideophones for research on language and perception.

Abstract

People often talk about musical pitch in terms of spatial metaphors. In English, for instance, pitches can be high or low, whereas in other languages pitches are described as thick or thin. According to psychophysical studies, metaphors in language can also shape people’s nonlinguistic space-pitch representations. But does language establish mappings between space and pitch in the first place or does it modify preexisting associations? Here we tested 4-month-old Dutch infants’ sensitivity to height-pitch and thickness-pitch mappings in two preferential looking tasks. Dutch infants looked significantly longer at cross-modally congruent stimuli in both experiments, indicating that infants are sensitive to space-pitch associations prior to language. This early presence of space-pitch mappings suggests that these associations do not originate from language. Rather, language may build upon pre-existing mappings and change them gradually via some form of competitive associative learning.

Abstract

Overview Since the early nineties, the on-going dramatic loss of the world’s linguistic diversity has gained attention, first by the linguists and increasingly also by the general public. As a response, the new field of language documentation emerged from around 2000 on, starting with the funding initiative ‘Dokumentation Bedrohter Sprachen’ (DoBeS, funded by the Volkswagen foundation, Germany), soon to be followed by others such as the ‘Endangered Languages Documentation Programme’ (ELDP, at SOAS, London), or, in the USA, ‘Electronic Meta-structure for Endangered Languages Documentation’ (EMELD, led by the LinguistList) and ‘Documenting Endangered Languages’ (DEL, by the NSF). From its very beginning, the new field focused on digital technologies not only for recording in audio and video, but also for annotation, lexical databases, corpus building and archiving, among others. This development not just coincides but is intrinsically interconnected with the increasing focus on digital data, technology and methods in all sciences, in particular in the humanities.

Abstract

This contribution presents “The Language Archive” (TLA), a new unit at the MPI for Psycholinguistics, discussing the current developments in management of scientific data, considering the need for new data research infrastructures. Although several initiatives worldwide in the realm of language resources aim at the integration, preservation and mobilization of research data, the state of such scientific data is still often problematic. Data are often not well organized and archived and not described by metadata ― even unique data such as field-work observational data on endangered languages is still mostly on perishable carriers. New data centres are needed that provide trusted, quality-reviewed, persistent services and suitable tools and that take legal and ethical issues seriously. The CLARIN initiative has established criteria for suitable centres. TLA is in a good position to be one of such centres. It is based on three essential pillars: (1) A data archive; (2) management, access and annotation tools; (3) archiving and software expertise for collaborative projects. The archive hosts mostly observational data on small languages worldwide and language acquisition data, but also data resulting from experiments

Abstract

Previous studies have shown that speakers align their speech to each other at multiple linguistic levels. This study investigates whether alignment is mostly the result of priming from the immediately preceding
speech materials, focussing on pitch and articulation rate (AR). Native Dutch speakers completed sentences, first by themselves (pre-test), then in alternation with Confederate 1 (Round 1), with Confederate 2 (Round 2), with Confederate 1 again
(Round 3), and lastly by themselves again (post-test). Results indicate that participants aligned to the confederates and that this alignment lasted during the post-test. The confederates’ directly preceding sentences were not good predictors for the participants’ pitch and AR. Overall, the results indicate that alignment is more of a global effect than a local priming effect.

Abstract

1. Introduction Speech conveys not only linguistic meaning but also paralinguistic information, such as features of the speaker’s social background, physiology, and emotional state. Linguistic and paralinguistic information is encoded in speech by using largely the same vocal apparatus and both are transmitted simultaneously in the acoustic signal, drawing on a limited set of acoustic cues. How this simultaneous encoding is achieved, how the different types of information are disentangled by the listener, and how much they interfere with one another is presently not well understood. Previous research has highlighted the importance of acoustic source and filter cues for emotion and linguistic encoding respectively, which may suggest that the two types of information are encoded independently of each other. However, those lines of investigation have been almost completely disconnected (Murray & Arnott, 1993).

Abstract

Language resource centers allow researchers to reliably deposit their structured data together with associated meta data and run services operating on this deposited data. We are looking into possibilities to create long-term persistency of both the deposited data and the services operating on this data. Challenges, both technical and non-technical, that need to be solved are the need to replicate more than just the data, proper identification of the digital objects in a distributed environment by making use of persistent identifiers and the set-up of a proper authentication and authorization domain including the management of the authorization information on the digital objects. We acknowledge the investment that most language resource centers have made in their current infrastructure. Therefore one of the most important requirements is the loose coupling with existing infrastructures without the need to make many changes. This shift from a single language resource center into a federated environment of many language resource centers is discussed in the context of a real world center: The Language Archive supported by the Max Planck Institute for Psycholinguistics.

Abstract

This paper shows that the dictation task, a well-
known testing instrument in language education, has
untapped potential as a research tool for studying
speech perception. We describe how transcriptions
can be scored on measures of lexical, orthographic,
phonological, and semantic similarity to target
phrases to provide comprehensive information about
accuracy at different processing levels. The former
three measures are automatically extractable,
increasing objectivity, and the middle two are
gradient, providing finer-grained information than
traditionally used. We evaluate the measures in an
English dictation task featuring phonetically reduced
continuous speech. Whereas the lexical and
orthographic measures emphasize listeners’ word
identification difficulties, the phonological measure
demonstrates that listeners can often still recover
phonological features, and the semantic measure
captures their ability to get the gist of the utterances.
Correlational analyses and a discussion of practical
and theoretical considerations show that combining
multiple measures improves the dictation task’s
utility as a research tool.

Abstract

Lexically guided perceptual learning has traditionally been studied with ambiguous consonant sounds to which native listeners are exposed in a purely receptive listening context. To extend previous research, we investigate whether lexically guided learning applies to a vowel shift encountered by non-native listeners in an interactive dialogue. Dutch participants played a two-player game in English in either a control condition, which contained no evidence for a vowel shift, or a lexically constraining condition, in which onscreen lexical information required them to re-interpret their interlocutor’s /ɪ/ pronunciations as representing /ε/. A phonetic categorization pre-test and post-test were used to assess whether the game shifted listeners’ phonemic boundaries such that more of the /ε/-/ɪ/ continuum came to be perceived as /ε/. Both listener groups showed an overall post-test shift toward /ɪ/, suggesting that vowel perception may be sensitive to directional biases related to properties of the speaker’s vowel space. Importantly, listeners in the lexically constraining condition made relatively more post-test /ε/ responses than the control group, thereby exhibiting an effect of lexically guided adaptation. The results thus demonstrate that non-native listeners can adjust their phonemic boundaries on the basis of lexical information to accommodate a vowel shift learned in interactive conversation.

Abstract

Achieving linguistic proficiency requires identifying words from speech, and discovering the constraints that govern the way those words are used. In a recent study of non-adjacent dependency learning, Frost and Monaghan (2016) demonstrated that learners may perform these tasks together, using similar statistical processes - contrary to prior suggestions. However, in their study, non-adjacent dependencies were marked by phonological cues (plosive-continuant-plosive structure), which may have influenced learning. Here, we test the necessity of these cues by comparing learning across three conditions; fixed phonology, which contains these cues, varied phonology, which omits them, and shapes, which uses visual shape sequences to assess the generality of statistical processing for these tasks. Participants segmented the sequences and generalized the structure in both auditory conditions, but learning was best when phonological cues were present. Learning was around chance on both tasks for the visual shapes group, indicating statistical processing may critically differ across domains.

Abstract

In many languages the future is in front and the past behind, but in some cultures (like Aymara) the past is in front. Is it possible to find this mapping as an alternative conceptualization of time in other cultures? If so, what are the factors that affect its choice out of the set of available alternatives? In a paper and pencil task, participants placed future or past events either in front or behind a character (a schematic head viewed from above). A sample of 24 Islamic participants (whose language also places the future in front and the past behind) tended to locate the past event in the front box more often than Spanish participants. This result might be due to the greater cultural value assigned to tradition in Islamic culture. The same pattern was found in a sample of Spanish elders (N = 58), what may support that conclusion. Alternatively, the crucial factor may be the amount of attention paid to the past. In a final study, young Spanish adults (N = 200) who had just answered a set of questions about their past showed the past-in-front pattern, whereas questions about their future exacerbated the future-in-front pattern. Thus, the attentional explanation was supported: attended events are mapped to front space in agreement with the experiential connection between attending and seeing. When attention is paid to the past, it tends to occupy the front location in spite of available alternative mappings in the language-culture.

Abstract

Large-scale graph data in real-world applications is often not static but dynamic,
i. e., new nodes and edges appear over time. Current graph convolution approaches
are promising, especially, when all the graph’s nodes and edges are available dur-
ing training. When unseen nodes and edges are inserted after training, it is not
yet evaluated whether up-training or re-training from scratch is preferable. We
construct an experimental setup, in which we insert previously unseen nodes and
edges after training and conduct a limited amount of inference epochs. In this
setup, we compare adapting pretrained graph neural networks against retraining
from scratch. Our results show that pretrained models yield high accuracy scores
on the unseen nodes and that pretraining is preferable over retraining from scratch.
Our experiments represent a first step to evaluate and develop truly online variants
of graph neural networks.

Abstract

Print Friendly XML Gebre, Binyam Gebrekidan, Max Planck Institute for Psycholinguistics, The Netherlands, binyamgebrekidan.gebre [at] mpi.nl Wittenburg, Peter, Max Planck Institute for Psycholinguistics, The Netherlands, peter.wittenburg [at] mpi.nl Introduction Many gesture and sign language researchers manually annotate video recordings to systematically categorize, analyze and explain their observations. The number and kinds of annotations are so diverse and unpredictable that any attempt at developing non-adaptive automatic annotation systems is usually less effective. The trend in the literature has been to develop models that work for average users and for average scenarios. This approach has three main disadvantages. First, it is impossible to know beforehand all the patterns that could be of interest to all researchers. Second, it is practically impossible to find enough training examples for all patterns. Third, it is currently impossible to learn a model that is robustly applicable across all video quality-recording variations.

Abstract

Automatic annotation of gesture strokes is important for many gesture and sign language researchers. The unpredictable diversity of human gestures and video recording conditions require that we adopt a more adaptive case-by-case annotation model. In this paper, we present a work-in progress annotation model that allows a user to a) track hands/face b) extract features c) distinguish strokes from non-strokes. The hands/face tracking is done with color matching algorithms and is initialized by the user. The initialization process is supported with immediate visual feedback. Sliders are also provided to support a user-friendly adjustment of skin color ranges. After successful initialization, features related to positions, orientations and speeds of tracked hands/face are extracted using unique identifiable features (corners) from a window of frames and are used for training a learning algorithm. Our preliminary results for stroke detection under non-ideal video conditions are promising and show the potential applicability of our methodology.

Abstract

Conversation requires a substantial amount of coordination between dialogue participants, from managing turn taking to negotiating mutual understanding. Part of this coordination effort surfaces as the reuse of linguistic behaviour across speakers, a process often referred to as alignment. While the presence of linguistic alignment is well documented in the literature, several questions remain open, including the extent to which patterns of reuse across speakers have an impact on the emergence of labelling conventions for novel referents. In this study, we put forward a methodology for automatically detecting shared lemmatised constructions---expressions with a common lexical core used by both speakers within a dialogue---and apply it to a referential communication corpus where participants aim to identify novel objects for which no established labels exist. Our analyses uncover the usage patterns of shared constructions in interaction and reveal that features such as their frequency and the amount of different constructions used for a referent are associated with the degree of object labelling convergence the participants exhibit after social interaction. More generally, the present study shows that automatically detected shared constructions offer a useful level of analysis to investigate the dynamics of reference negotiation in dialogue.

Abstract

Gestures are integral components of face-to-face communication. They unfold over time, often following predictable movement phases of preparation, stroke, and re-
traction. Yet, the prevalent approach to automatic gesture detection treats the problem as binary classification, classifying a segment as either containing a gesture or not, thus failing to capture its inherently sequential and contextual nature. To address this, we introduce a novel framework that reframes the task as a multi-phase sequence labeling problem rather than binary classification. Our model processes sequences of skeletal movements over time windows, uses Transformer encoders to learn contextual embeddings, and leverages Conditional Random Fields to perform sequence labeling. We evaluate our proposal on a large dataset of diverse co-speech gestures in task-oriented face-to-face dialogues. The results consistently demonstrate that our method significantly outperforms strong baseline models in detecting gesture strokes. Furthermore, applying Transformer encoders to learn contextual embeddings from movement sequences substantially improves gesture unit detection. These results highlight our framework’s capacity to capture the fine-grained dynamics of co-speech gesture phases, paving the way for more nuanced and accurate gesture detection and analysis.

Abstract

Recognizing the speech acts in our interlocutors’ utterances is a crucial prerequisite for conversation. However, it is not a trivial task given that the form and content of utterances is frequently underspecified for this level of meaning. In the present study we investigate participants’ competence in categorizing speech acts in such action-underspecific sentences and explore the time-course of speech act inferencing using a self-paced reading paradigm. The results demonstrate that participants are able to categorize the speech acts with very high accuracy, based on limited context and without any prosodic information. Furthermore, the results show that the exact same sentence is processed differently depending on the speech act it performs, with reading times starting to differ already at the first word. These results indicate that participants are very good at “getting” the speech acts, opening up a new arena for experimental research on action recognition in conversation.

Abstract

The standard for the analysis of distorted voices is perceptual rating of read-out texts or spontaneous speech. Automatic voice evaluation, however, is usually done on stable sections of sustained vowels. In this paper, text-based and established vowel-based analysis are compared with respect to their ability to measure hoarseness and its subclasses. 73 hoarse patients (48.3±16.8 years) uttered the vowel /e/ and read the German version of the text “The North Wind and the Sun”. Five speech therapists and physicians rated roughness, breathiness, and hoarseness according to the German RBH evaluation scheme. The best human-machine correlations were obtained for measures based on the Cepstral Peak Prominence (CPP; up to |r | = 0.73). Support Vector Regression (SVR) on CPP-based measures and prosodic features improved the results further to r ≈0.8 and confirmed that automatic voice evaluation should be performed on a text recording.

Abstract

Child songs are a great source for linguistic learning. Here we explore whether children can acquire novel words in a second language by playing a game featuring child songs in a playhouse. We present data from three studies that serve as scientific proof for the functionality of one game of the playhouse: the Energy Center. For this game, three hand-bikes were mounted on a panel. When children start moving the hand-bikes, child songs start playing simultaneously. Once the children produce enough energy with the hand-bikes, the songs are additionally accompanied with the sounds of musical instruments. In our studies, children executed a picture-selection task to evaluate whether they acquired new vocabulary from the songs presented during the game. Two of our studies were run in the field, one at a Dutch and one at an Indian pre-school. The third study features data from a more controlled laboratory setting. Our results partly confirm that the Energy Center is a successful means to support vocabulary acquisition in a second language. More research with larger sample sizes and longer access to the Energy Center is needed to evaluate the overall functionality of the game. Based on informal observations at our test sites, however, we are certain that children do pick up linguistic content from the songs during play, as many of the children repeat words and phrases from songs they heard. We will pick up upon these promising observations during future studies

Abstract

This study investigated whether a shadowing task can provide insights in the nature of reduction processes that are typical of casual speech. We focused on the shortening and presence versus absence of schwa and /t/ in Dutch past participles. Results showed that the absence of these segments was affected by the same variables as their shortening, suggesting that absence mostly resulted from extreme gradient shortening. This contrasts with results based on recordings of spontaneous conversations. We hypothesize that this difference is due to non-casual fast speech elicited by a shadowing task.

Abstract

Prediction in language has traditionally been studied using
simple designs in which neural responses to expected
and unexpected words are compared in a categorical
fashion. However, these designs have been contested
as being ‘prediction encouraging’, potentially exaggerating
the importance of prediction in language understanding.
A few recent studies have begun to address
these worries by using model-based approaches to probe
the effects of linguistic predictability in naturalistic stimuli
(e.g. continuous narrative). However, these studies
so far only looked at very local forms of prediction, using
models that take no more than the prior two words into
account when computing a word’s predictability. Here,
we extend this approach using a state-of-the-art neural
language model that can take roughly 500 times longer
linguistic contexts into account. Predictability estimates
fromthe neural network offer amuch better fit to EEG data
from subjects listening to naturalistic narrative than simpler
models, and reveal strong surprise responses akin to
the P200 and N400. These results show that predictability
effects in language are not a side-effect of simple designs,
and demonstrate the practical use of recent advances
in AI for the cognitive neuroscience of language.

Abstract

Co-speech gestures are an integral part of human face-to-face communication, but little is known about how pragmatic factors influence our comprehension of those gestures. The present study investigates how different types of recipients process iconic gestures in a triadic communicative situation. Participants (N = 32) took on the role of one of two recipients in a triad and were presented with 160 video clips of an actor speaking, or speaking and gesturing. Crucially, the actor’s eye gaze was manipulated in that she alternated her gaze between the two recipients. Participants thus perceived some messages in the role of addressed recipient and some in the role of unaddressed recipient. In these roles, participants were asked to make judgements concerning the speaker’s messages. Their reaction times showed that unaddressed recipients did comprehend speaker’s gestures differently to addressees. The findings are discussed with respect to automatic and controlled processes involved in gesture comprehension.

Abstract

This study investigates effects of prosodic factors (prominence, boundary) on coarticulatory Vnasalization in Australian English (AusE) in CVN and NVC in comparison to those in American English
(AmE). As in AmE, prominence was found to
lengthen N, but to reduce V-nasalization, enhancing N’s nasality and V’s orality, respectively (paradigmatic contrast enhancement). But the prominence effect in CVN was more robust than that in AmE. Again similar to findings in AmE, boundary
induced a reduction of N-duration and V-nasalization phrase-initially (syntagmatic contrast enhancement), and increased the nasality of both C and V phrasefinally.
But AusE showed some differences in terms
of the magnitude of V nasalization and N duration. The results suggest that the linguistic contrast enhancements underlie prosodic-structure modulation of coarticulatory V-nasalization in
comparable ways across dialects, while the fine phonetic detail indicates that the phonetics-prosody interplay is internalized in the individual dialect’s phonetic grammar.

Abstract

Indian Sign Language has limited resources for developing machine learning and data-driven approaches for automated language processing. Though text/audio-based language processing techniques have shown colossal research interest and tremendous improvements in the last few years, Sign Languages still need to catch up due to the need for more resources. To bridge this gap, in this work, we propose iSign: a benchmark for Indian Sign Language (ISL) Processing. We make three primary contributions to this work. First, we release one of the largest ISL-English datasets with more than video-sentence/phrase pairs. To the best of our knowledge, it is the largest sign language dataset available for ISL. Second, we propose multiple NLP-specific tasks (including SignVideo2Text, SignPose2Text, Text2Pose, Word Prediction, and Sign Semantics) and benchmark them with the baseline models for easier access to the research community. Third, we provide detailed insights into the proposed benchmarks with a few linguistic insights into the working of ISL. We streamline the evaluation of Sign Language processing, addressing the gaps in the NLP research community for Sign Languages. We release the dataset, tasks and models via the following website: https://exploration-lab.github.io/iSign/

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

The past year has seen a steep rise in generative AI systems that claim to be open. But how open are they really? The question of what counts as open source in generative AI is poised to take on particular importance in light of the upcoming EU AI Act that regulates open source systems differently, creating an urgent need for practical openness assessment. Here we use an evidence-based framework that distinguishes 14 dimensions of openness, from training datasets to scientific and technical documentation and from licensing to access methods. Surveying over 45 generative AI systems (both text and text-to-image), we find that while the term open source is widely used, many models are `open weight' at best and many providers seek to evade scientific, legal and regulatory scrutiny by withholding information on training and fine-tuning data. We argue that openness in generative AI is necessarily composite (consisting of multiple elements) and gradient (coming in degrees), and point out the risk of relying on single features like access or licensing to declare models open or not. Evidence-based openness assessment can help foster a generative AI landscape in which models can be effectively regulated, model providers can be held accountable, scientists can scrutinise generative AI, and end users can make informed decisions.

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

Speakers and listeners show an informativity bias in the use and interpretation of color modifiers. For example, speakers use color more often when referring to objects that vary in color than to objects with a prototypical color. Likewise, listeners look away from objects with prototypical colors upon hearing that color mentioned. Here we test whether speakers and listeners account for another factor related to informativity: the strength of the association between lexical categories and color. Our results demonstrate that speakers and listeners' choices are indeed influenced by this factor; as such, it should be integrated into current pragmatic theories of informativity and computational models of color reference.

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

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

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

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

Human conversations are inherently multimodal, including auditory speech, visual articulatory cues, and hand gestures. Recent studies demonstrated that the timing of a simple up-and-down hand movement, known as a beat gesture, can affect speech perception. A beat gesture falling on the first syllable of a disyllabic word induces a bias to perceive a strong-weak stress pattern (i.e., “CONtent”), while a beat gesture falling on the second syllable combined with the same acoustics biases towards a weak-strong stress pattern (“conTENT”). This effect, termed the “manual McGurk effect”, has been studied in both in-lab and online studies, employing standard experimental sessions lasting approximately forty minutes. The present work tests whether the manual McGurk effect can be observed in an online short version (“mini-test”) of the original paradigm, lasting only ten minutes. Additionally, we employ two different response modalities, namely a two-alternative forced choice and a visual analog scale. A significant manual McGurk effect was observed with both response modalities. Overall, the present study demonstrates the feasibility of employing a ten-minute manual McGurk mini-test to obtain a measure of gesture-speech integration. As such, it may lend itself for inclusion in large-scale test batteries that aim to quantify individual variation in language processing.

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

With the recent advancements in the field of robotics and the increased focus on having general-purpose robots widely available to the general public, it has become increasingly necessary to pursue research into Human-robot interaction (HRI). While there have been a lot of works discussing frameworks for teaching HRI in educational institutions with a few institutions already offering courses to students, a consensus on the course content still eludes the field. In this work, we highlight a few challenges and opportunities while designing an HRI course from an Indian perspective. These topics warrant further deliberations as they have a direct impact on the design of HRI courses and wider implications for the entire field.

Abstract

The anterior lordosis of the cervical spine is thought
to contribute to pitch (fo) production by influencing
cricoid rotation as a function of larynx height. This
study examines the matter of inter-individual
variation in cervical spine shape and whether this has
an influence on how fo is produced along increasing
or decreasing scales, using the ArtiVarK dataset,
which contains real-time MRI pitch production data.
We find that the cervical spine actively participates in
fo production, but the amount of displacement
depends on individual shape. In general, anterior
spine motion (tending toward cervical lordosis)
occurs for low fo, while posterior movement (tending
towards cervical kyphosis) occurs for high fo.

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

In order to study the cognitive processes underlying speech comprehension, neuro-physiological measures (e.g., EEG and MEG), or behavioural measures (e.g., reaction times and response accuracy) can be applied. Compared to behavioural measures, EEG signals can provide a more fine-grained and complementary view of the processes that take place during the unfolding of an auditory stimulus.

EEG signals are often analysed after having chosen specific time windows, which are usually based on the temporal structure of ERP components expected to be sensitive to the experimental manipulation. However, as the timing of ERP components may vary between experiments, trials, and participants, such a-priori defined analysis time windows may significantly hamper the exploratory power of the analysis of components of interest. In this paper, we explore a wide-window analysis method applied to EEG signals collected in an auditory repetition priming experiment.

This approach is based on a bank of temporal filters arranged along the time axis in combination with linear mixed effects modelling. Crucially, it permits a temporal decomposition of effects in a single comprehensive statistical model which captures the entire EEG trace.

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

This paper describes recent experimental evidence which shows that models of spoken word recognition must incorporate both inhibition between competing lexical candidates and a sensitivity to metrical cues to lexical segmentation. A new version of the Shortlist [1][2] model incorporating the Metrical Segmentation Strategy [3] provides a detailed simulation of the data.

Abstract

-* indicates shared first authorship -
The present study investigated the effects of selective attention on the processing of morphosyntactic errors in unattended parts of speech. Two groups of German native (L1) speakers participated in the present study. Participants listened to sentences in which irregular verbs were manipulated in three different conditions (correct, incorrect but attested ablaut pattern, incorrect and crosslinguistically unattested ablaut pattern). In order to track fast dynamic neural reactions to the stimuli, electroencephalography was used. After each sentence, participants in Experiment 1 performed a semantic judgement task, which deliberately distracted the participants from the syntactic manipulations and directed their attention to the semantic content of the sentence. In Experiment 2, participants carried out a syntactic judgement task, which put their attention on the critical stimuli. The use of two different attentional tasks allowed for investigating the impact of selective attention on speech processing and whether morphosyntactic processing steps are performed automatically. In Experiment 2, the incorrect attested condition elicited a larger N400 component compared to the correct condition, whereas in Experiment 1 no differences between conditions were found. These results suggest that the processing of morphosyntactic violations in irregular verbs is not entirely automatic but seems to be strongly affected by selective attention.

Abstract

Natural speech involves repair. These repairs are often highlighted through prosodic marking (Levelt & Cutler, 1983). Prosodic marking usually entails an increase in pitch, loudness, and/or duration that draws attention to the corrected word. While it is established that natural self-repairs typically elicit prosodic marking, the exact cause of this is unclear. This study investigates whether producing a prosodic marking emerges from an automatic correction process or has a communicative purpose. In the current study, we elicit corrections to test whether all self-corrections elicit prosodic marking. Participants carried out a picture-naming task in which they described two images presented on-screen. To prompt self-correction, the second image was altered in some cases, requiring participants to abandon their initial utterance and correct their description to match the new image. This manipulation was compared to a control condition in which only the orientation of the object would change, eliciting no self-correction while still presenting a visual change. We found that the replacement of the item did not elicit a prosodic marking, regardless of the type of change. Theoretical implications and research directions are discussed, in particular theories of prosodic planning.

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

Spontaneously occurring speech is often seamlessly accompanied by hand gestures. Detailed
observations of video data suggest that speech and gesture are tightly synchronized in time,
consistent with a dynamic interplay between body and mind. However, spontaneous gesturespeech
synchrony has rarely been objectively quantified beyond analyses of video data, which
do not allow for identification of kinematic properties of gestures. Consequently, the point in
gesture which is held to couple with speech, the so-called moment of “maximum effort”, has
been variably equated with the peak velocity, peak acceleration, peak deceleration, or the onset
of the gesture. In the current exploratory report, we provide novel evidence from motiontracking
and acoustic data that peak velocity is closely aligned, and shortly leads, the peak pitch
(F0) of speech