Publications

Abstract

In this work we perform multimodal detection and classification
of head movements from face to face video conversation data.
We have experimented with different models and feature sets
and provided some insight on the effect of independent features,
but also how their interaction can enhance a head movement
classifier. Used features include nose, neck and mid hip position
coordinates and their derivatives together with acoustic features,
namely, intensity and pitch of the speaker on focus. Results
show that when input features are sufficiently processed by in-
teracting with each other, a linear classifier can reach a similar
performance to a more complex non-linear neural model with
several hidden layers. Our best models achieve state-of-the-art
performance in the detection task, measured by macro-averaged
F1 score.

Abstract

Continuous vector word representations (or
word embeddings) have shown success in cap-turing semantic relations between words, as evidenced by evaluation against behavioral data of adult performance on semantic tasks (Pereira et al., 2016). Adult semantic knowl-edge is the endpoint of a language acquisition process; thus, a relevant question is whether these models can also capture emerging word
representations of young language learners. However, the data for children’s semantic knowledge across development is scarce. In this paper, we propose to bridge this gap by using Age of Acquisition norms to evaluate word embeddings learnt from child-directed input. We present two methods that evaluate word embeddings in terms of (a) the semantic neighbourhood density of learnt words, and (b) con-
vergence to adult word associations. We apply our methods to bag-of-words models, and find that (1) children acquire words with fewer semantic neighbours earlier, and (2) young learners only attend to very local context. These findings provide converging evidence for validity of our methods in understanding the prerequisite features for a distributional model of word learning.

Abstract

The present paper assesses discourse-pragmatic factors as a potential explanation for the subject-object assymetry in early child language. It identifies a set of factors which characterize typical situations of informativeness (Greenfield & Smith, 1976), and uses these factors to identify informative arguments in data from four children aged 2;0 through 3;6 learning Inuktitut as a first language. In addition, it assesses the extent of the links between features of informativeness on one hand and lexical vs. null and subject vs. object arguments on the other. Results suggest that a pragmatics account of the subject-object asymmetry can be upheld to a greater extent than previous research indicates, and that several of the factors characterizing informativeness are good indicators of those arguments which tend to be omitted in early child language.

Abstract

The term “uptalk” describes utterance-final pitch rises that carry no sentence-structural information. Uptalk is usually dialectal or sociolectal, and Australian English (AusEng) is particularly known for this attribute. We ask here whether experience with an uptalk variety affects listeners’ ability to categorise rising pitch contours on the basis of the timing and height of their onset and offset. Listeners were two groups of English-speakers (AusEng, and American English), and three groups of listeners with L2 English: one group with Mandarin as L1 and experience of listening to AusEng, one with German as L1 and experience of listening to AusEng, and one with German as L1 but no AusEng experience. They heard nouns (e.g. flower, piano) in the framework “Got a NOUN”, each ending with a pitch rise artificially manipulated on three contrasts: low vs. high rise onset, low vs. high rise offset and early vs. late rise onset. Their task was to categorise the tokens as “question” or “statement”, and we analysed the effect of the pitch contrasts on their judgements. Only the native AusEng listeners were able to use the pitch contrasts systematically in making these categorisations.

Abstract

In order to understand early word learning we need to better understand and quantify properties of the input that young children receive. We extended the human simulation paradigm (HSP) using egocentric videos taken from infant head-mounted cameras. The videos were further annotated with gaze information indicating in-the-moment visual attention from the infant. Our new HSP prompted participants for two types of responses, thus differentiating referential from semantic ambiguity in the learning input. Consistent with findings on visual attention in word learning, we find a strongly bimodal distribution over HSP accuracy. Even in this open-ended task, most videos only lead to a small handful of common responses. What's more, referential ambiguity was the key bottleneck to performance: participants can nearly always recover the exact word that was said if they identify the correct referent. Finally, analysis shows that adult learners relied on particular, multimodal behavioral cues to infer those target referents.

Abstract

This paper reports a perceptual study using a semantically motivated identification task in which we investigated the nature of two pairs of intonational contrasts in English: (1) normal High accent vs. emphatic High accent; (2) early peak alignment vs. late peak alignment. Unlike previous inquiries, the present study employs an on-line method using the Reaction Time measurement, in addition to the measurement of response frequencies. Regarding the peak height continuum, the mean RTs are shortest for within-category identification but longest for across-category identification. As for the peak alignment contrast, no identification boundary emerges and the mean RTs only reflect a difference between peaks aligned with the vowel onset and peaks aligned elsewhere. We conclude that the peak height contrast is discrete but the previously claimed discreteness of the peak alignment contrast is not borne out.

Abstract

In this study, we analyze one French signing and one French speaking family’s interaction during dinner. The families composed of two parents and two children aged 3 to 11 were filmed with three cameras to capture all family members’ behaviors. The three videos per dinner were synchronized and coded on ELAN. We annotated all participants’ acting, and languaging.
Our quantitative analyses show how family members collaboratively manage multiple streams of activity through the embodied performances of dining and interacting. We uncover different profiles according to participants’ modality of expression and status (focusing on the mother and the younger child). The hearing participants’ co-activity management illustrates their monitoring of dining and conversing and how they progressively master the affordances of the visual and vocal channels to maintain the simultaneity of the two activities. The deaf mother skillfully manages to alternate smoothly between dining and interacting. The deaf younger child manifests how she is in the process of developing her skills to manage multi-activity. Our qualitative analyses focus on the ecology of visual-gestural and audio-vocal languaging in the context of co-activity according to language and participant. We open new perspectives on the management of gaze and body parts in multimodal languaging.

Abstract

This study examines the effects of prosodic boundaries, lexical stress, and phrasal accent on the acoustic realization of stops (/t, d/) in Dutch, with special attention paid to language-specificity in the phonetics-prosody interface. The results obtained from various acoustic measures show systematic phonetic variations in the production of /t d/ as a function of prosodic position, which may be interpreted as being due to prosodicallyconditioned articulatory strengthening. Shorter VOTs were found for the voiceless stop /t/ in prosodically stronger locations (as opposed to longer VOTs in this position in English). The results suggest that prosodically-driven phonetic realization is bounded by a language-specific phonological feature system.

Abstract

Listeners rely on native-language rhythm in segmenting speech; in different languages, stress-, syllable- or mora-based rhythm is exploited. This language-specificity affects listening to non- native speech, if native procedures are applied even though inefficient for the non-native language. However, speakers of two languages with similar rhythmic interpretation should segment their own and the other language similarly. This was observed to date only for related languages (English-Dutch; French-Spanish). We now report experiments in which Japanese listeners heard Telugu, a Dravidian language unrelated to Japanese, and Telugu listeners heard Japanese. In both cases detection of target sequences in speech was harder when target boundaries mismatched mora boundaries, exactly the pattern that Japanese listeners earlier exhibited with Japanese and other languages. These results suggest that Telugu and Japanese listeners use similar procedures in segmenting speech, and support the idea that languages fall into rhythmic classes, with aspects of phonological structure affecting listeners' speech segmentation.

Abstract

Assimilation of place of articulation across a nasal and a following stop consonant is obligatory in Japanese, but not in Dutch. In four experiments the processing of assimilated forms by speakers of Japanese and Dutch was compared, using a task in which listeners blended pseudo-word pairs such as ranga-serupa. An assimilated blend of this pair would be rampa, an unassimilated blend rangpa. Japanese listeners produced significantly more assimilated than unassimilated forms, both with pseudo-Japanese and pseudo-Dutch materials, while Dutch listeners produced significantly more unassimilated than assimilated forms in each materials set. This suggests that Japanese listeners, whose native-language phonology involves obligatory assimilation constraints, represent the assimilated nasals in nasal-stop sequences as unmarked for place of articulation, while Dutch listeners, who are accustomed to hearing unassimilated forms, represent the same nasal segments as marked for place of articulation.

Abstract

A distinction between strong and weak vowels can be drawn on the basis of vowel quality, of stress, or of both factors. An experiment was conducted in which sets of contextually matched word-intial vowels ranging from clearly strong to clearly weak were cross-spliced, and the naturalness of the resulting words was rated by listeners. The ratings showed that in general cross-spliced words were only significantly less acceptable than unspliced words when schwa was not involved; this supports a categorical distinction based on vowel quality.

Abstract

Previous research has shown that listeners use the prosodic structure of utterances in a predictive fashion in sentence comprehension, to direct attention to accented words. Acoustically identical words spliced into sentence contexts arc responded to differently if the prosodic structure of the context is \ aricd: when the preceding prosody indicates that the word will he accented, responses are faster than when the preceding prosodv is inconsistent with accent occurring on that word. In the present series of experiments speech hybridisation techniques were first used to interchange the timing patterns within pairs of prosodic variants of utterances, independently of the pitch and intensity contours. The time-adjusted utterances could then serve as a basis lor the orthogonal manipulation of the three prosodic dimensions of pilch, intensity and rhythm. The overall pattern of results showed that when listeners use prosody to predict accent location, they do not simply rely on a single prosodic dimension, hut exploit the interaction between pitch, intensity and rhythm.

Abstract

Languages contain tens of thousands of words, but these are constructed from a tiny handful of phonetic elements. Consequently, words resemble one another, or can be embedded within one another, a coup stick snot with standing. me process of spoken-word recognition by human listeners involves activation of multiple word candidates consistent with the input, and direct competition between activated candidate words. Further, human listeners are sensitive, at an early, prelexical, stage of speeeh processing, to constraints on what could potentially be a word of the language.

Abstract

The phoneme detection task is widely used in spoken word recognition research. Alphabetically literate participants, however, are more used to explicit representations of letters than of phonemes. The present study explored whether phoneme detection is sensitive to how target phonemes are, or may be, orthographically realised. Listeners detected the target sounds [b,m,t,f,s,k] in word-initial position in sequences of isolated English words. Response times were faster to the targets [b,m,t], which have consistent word-initial spelling, than to the targets [f,s,k], which are inconsistently spelled, but only when listeners’ attention was drawn to spelling by the presence in the experiment of many irregularly spelled fillers. Within the inconsistent targets [f,s,k], there was no significant difference between responses to targets in words with majority and minority spellings. We conclude that performance in the phoneme detection task is not necessarily sensitive to orthographic effects, but that salient orthographic manipulation can induce such sensitivity.

Abstract

Two lexical decision experiments in Cantonese are described in which the recognition of spoken target words as a function of phonological similarity to a preceding prime is investigated. Phonological similaritv in first syllables produced inhibition, while similarity in second syllables led to facilitation. Differences between syllables in tonal and segmental structure had generally similar effects.

Abstract

Speakers and listeners have a shared goal: to communicate. The processes of speech perception and of speech production interact in many ways under the constraints of this communicative goal; such interaction is as characteristic of prosodic processing as of the processing of other aspects of linguistic structure. Two of the major uses of prosodic information in situations of communication are to encode salience and segmentation, and these themes unite the contributions to the symposium introduced by the present review.

Abstract

Humans readily generalize, applying prior knowledge to novel situations and stimuli. Advances in machine learning have begun to approximate and even surpass human performance, but these systems struggle to generalize what they have learned to untrained situations. We present a model based on wellestablished neurocomputational principles that demonstrates human-level generalisation. This model is trained to play one video game (Breakout) and performs one-shot generalisation to a new game (Pong) with different characteristics. The model
generalizes because it learns structured representations that are functionally symbolic (viz., a role-filler binding calculus) from unstructured training data. It does so without feedback, and without requiring that structured representations are specified a priori. Specifically, the model uses neural co-activation to discover which characteristics of the input are invariant and to learn relational predicates, and oscillatory regularities in network firing to bind predicates to arguments. To our knowledge,
this is the first demonstration of human-like generalisation in a machine system that does not assume structured representa-
tions to begin with.

Abstract

This paper summarizes the results of a descriptive syntactic category analysis of child English no which reveals that young children use and represent no as a determiner and negatives like no pen as NPs, contra standard analyses.

Abstract

This paper presents Advanced Glossing, a proposal for a general glossing format designed for language documentation, and a specific setup for the Shoebox-program that implements Advanced Glossing to a large extent. Advanced Glossing (AG) goes beyond the traditional Interlinear Morphemic Translation, keeping syntactic and morphological information apart from each other in separate glossing tables. AG provides specific lines for different kinds of annotation – phonetic, phonological, orthographical, prosodic, categorial, structural, relational, and semantic, and it allows for gradual and successive, incomplete, and partial filling in case that some information may be irrelevant, unknown or uncertain. The implementation of AG in Shoebox sets up several databases. Each documented text is represented as a file of syntactic glossings. The morphological glossings are kept in a separate database. As an additional feature interaction with lexical databases is possible. The implementation makes use of the interlinearizing automatism provided by Shoebox, thus obtaining the table format for the alignment of lines in cells, and for semi-automatic filling-in of information in glossing tables which has been extracted from databases

Abstract

Digitizing and annotating texts and field recordings Given that several initiatives worldwide currently explore the new field of documentation of endangered languages, the E-MELD project proposes to survey and unite procedures, techniques and results in order to achieve its main goal, ''the formulation and promulgation of best practice in linguistic markup of texts and lexicons''. In this context, this year's workshop deals with the processing of recorded texts. I assume the most valuable contribution I could make to the workshop is to show the procedures and methods used in the Awetí Language Documentation Project. The procedures applied in the Awetí Project are not necessarily representative of all the projects in the DOBES program, and they may very well fall short in several respects of being best practice, but I hope they might provide a good and concrete starting point for comparison, criticism and further discussion. The procedures to be exposed include: * taping with digital devices, * digitizing (preliminarily in the field, later definitely by the TIDEL-team at the Max Planck Institute in Nijmegen), * segmenting and transcribing, using the transcriber computer program, * translating (on paper, or while transcribing), * adding more specific annotation, using the Shoebox program, * converting the annotation to the ELAN-format developed by the TIDEL-team, and doing annotation with ELAN. Focus will be on the different types of annotation. Especially, I will present, justify and discuss Advanced Glossing, a text annotation format developed by H.-H. Lieb and myself designed for language documentation. It will be shown how Advanced Glossing can be applied using the Shoebox program. The Shoebox setup used in the Awetí Project will be shown in greater detail, including lexical databases and semi-automatic interaction between different database types (jumping, interlinearization). ( Freie Universität Berlin and Museu Paraense Emílio Goeldi, with funding from the Volkswagen Foundation.)

Abstract

Traditionally, there have been three standard assumptions made about the Parallelism Effect on VP-ellipsis, namely that the effect is categorical, that it applies asymmetrically and that it is uniquely due to syntactic factors. Based on the results of a series of experiments involving online and offline tasks, it will be argued that the Parallelism Effect is instead noncategorical and interactional. The factors investigated include construction type, conceptual and morpho-syntactic recoverability, finiteness and anaphor type (to test VP-anaphora). The results show that parallelism is gradient rather than categorical, effects both VP-ellipsis and anaphora, and is influenced by both structural and non-structural factors.

Abstract

The study presented here focuses on two pragmatic gestures:
the hand flip (Ferré, 2011), a gesture of the Palm Up Open
Hand/PUOH family (Müller, 2004) and the closed hand which
can be considered as the opposite kind of movement to the open-
ing of the hands present in the PUOH gesture. Whereas one of
the functions of the hand flip has been described as presenting
a new point in speech (Cienki, 2021), the closed hand gesture
has not yet been described in the literature to the best of our
knowledge. It can however be conceived of as having the oppo-
site function of announcing the end of a point in discourse. The
object of the present study is therefore to determine, with the
study of prosodic features, if the two gestures are found in the
same type of speech units and what their respective scope is.
Drawing from a corpus of three TED Talks in French the
prosodic characteristics of the speech that accompanies the two
gestures will be examined. The hypothesis developed in the
present paper is that their scope should be reflected in the
prosody of accompanying speech, especially pitch key, tone,
and relative pitch range. The prediction is that hand flips and
closing hand gestures are expected to be located at the periph-
ery of Intonation Phrases (IPs), Inter-Pausal Units (IPUs) or
more conversational Turn Constructional Units (TCUs), and are
likely to be co-occurrent with pauses in speech. But because of
the natural slope of intonation in speech, the speech that accom-
pany early gestures in Intonation Phrases should reveal different
features from the speech at the end of intonational units. Tones
should be different as well, considering the prosodic structure
of spoken French.

Abstract

The last few years have revealed that several species may share the building blocks of Musicality with humans. The recognition of these building blocks (e.g., rhythm, frequency variation) was a necessary impetus for a new round of studies investigating rhythmic variation in animal vocal displays. Singing primates are a small group of primate species that produce modulated songs ranging from tens to thousands of vocal units. Previous studies showed that the indri, the only singing lemur, is currently the only known species that perform duet and choruses showing multiple rhythmic categories, as seen in human music. Rhythmic categories occur when temporal intervals between note onsets are not uniformly distributed, and rhythms with a small integer ratio between these intervals are typical of human music. Besides indris, white-handed gibbons and three crested gibbon species showed a prominent rhythmic category corresponding to a single small integer ratio, isochrony. This study reviews previous evidence on the co-occurrence of rhythmic categories in primates and focuses on the prospects for a comparative, multimodal study of rhythmicity in this clade.

Abstract

Despite the early emergence of pointing, children are generally not documented to produce iconic gestures until later in development. Although research has described this developmental trajectory and the types of iconic gestures that emerge first, there has been limited focus on iconic gestures within interactional contexts. This study identified the first 10 iconic gestures produced by five monolingual English-speaking children in a naturalistic longitudinal video corpus and analysed the interactional contexts. We found children produced their first iconic gesture between 12 and 20 months and that gestural types varied. Although 34% of gestures could have been imitated or derived from adult or child actions in the preceding context, the majority were produced independently of any observed model. In these cases, adults often led the interaction in a direction where iconic gesture was an appropriate response. Overall, we find infants can represent a referent symbolically and possess a greater capacity for innovation than previously assumed. In order to develop our understanding of how children learn to produce iconic gestures, it is important to consider the immediate interactional context. Conducting naturalistic corpus analyses could be a more ecologically valid approach to understanding how children learn to produce iconic gestures in real life contexts.

Abstract

Face to face interaction is fundamental to human sociality but is very complex to study in a scientific fashion. This theme issue brings together cutting-edge approaches to the study of face-to-face interaction and showcases how we can make progress in this area. Researchers are now studying interaction in adult conversation, parent-child relationships, neurodiverse groups, interactions with virtual agents and various animal species. The theme issue reveals how new paradigms are leading to more ecologically grounded and comprehensive insights into what social interaction is. Scientific advances in this area can lead to improvements in education and therapy, better understanding of neurodiversity and more engaging artificial agents

Abstract

There is evidence that the process of executing a planned utterance involves the use of both preceding-context and top-down cues. Utterance-initial words are cued only by the top-down plan. In contrast, non-initial words are cued both by top-down cues and preceding-context cues. Co-existence of both cue types raises the question of how they interact during learning. We argue that this interaction is competitive: items that tend to be preceded by predictive preceding-context cues are harder to activate from the plan without this predictive context. A novel computational model of this competition is developed. The model is tested on a corpus of repetition disfluencies and shown to account for the influences on patterns of restarts during production. In particular, this model predicts a novel Initiation Effect: following an interruption, speakers re-initiate production from words that tend to occur in utterance-initial position, even when they are not initial in the interrupted utterance.

Abstract

The representations generated by many mod-
els of language (word embeddings, recurrent
neural networks and transformers) correlate
to brain activity recorded while people read.
However, these decoding results are usually
based on the brain’s reaction to syntactically
and semantically sound language stimuli. In
this study, we asked: how does an LSTM (long
short term memory) language model, trained
(by and large) on semantically and syntac-
tically intact language, represent a language
sample with degraded semantic or syntactic
information? Does the LSTM representation
still resemble the brain’s reaction? We found
that, even for some kinds of nonsensical lan-
guage, there is a statistically significant rela-
tionship between the brain’s activity and the
representations of an LSTM. This indicates
that, at least in some instances, LSTMs and the
human brain handle nonsensical data similarly.

Abstract

This special publication aims to build a renewed enthusiasm for collecting acquisition data across many languages, including those facing endangerment and loss. It presents a guide for documenting and describing child language and child-directed language in diverse languages and cultures, as well as a collection of acquisition sketches based on this guide. The guide is intended for anyone interested in working across child language and language documentation, including, for example, field linguists and language documenters, community language workers, child language researchers or graduate students.

Abstract

Most bioacoustics software is used to analyse the already collected acoustics data in batch, i.e., after the data-collecting phase of a scientific study. However, experiments based on animal training require immediate and precise reactions from the experimenter, and thus do not easily dovetail with a typical bioacoustics workflow. Bridging this methodological gap, we have developed a custom application to live-monitor the vocal development of harbour seals in a behavioural experiment. In each trial, the application records and automatically detects an animal's call, and immediately measures duration and acoustic measures such as intensity, fundamental frequency, or formant frequencies. It then displays a spectrogram of the recording and the acoustic measurements, allowing the experimenter to instantly evaluate whether or not to reinforce the animal's vocalisation. From a technical perspective, the rapid and easy development of this custom software was made possible by combining multiple open-source software projects. Here, we integrated the acoustic analyses from Parselmouth, a Python library for Praat, together with PyAudio and Matplotlib's recording and plotting functionality, into a custom graphical user interface created with PyQt. This flexible recombination of different open-source Python libraries allows the whole program to be written in a mere couple of hundred lines of code

Abstract

Sign language is a rich form of communication, uniquely conveying meaning through a combination of gestures, facial expressions, and body movements. Existing research in sign language generation has predominantly focused on text-to-sign pose generation, while speech-to-sign pose generation remains relatively underexplored. Speech-to-sign language generation models can facilitate effective communication between the deaf and hearing communities. In this paper, we propose an architecture that utilises prosodic information from speech audio and semantic context from text to generate sign pose sequences. In our approach, we adopt a multi-tasking strategy that involves an additional task of predicting Facial Action Units (FAUs). FAUs capture the intricate facial muscle movements that play a crucial role in conveying specific facial expressions during sign language generation. We train our models on an existing Indian Sign language dataset that contains sign language videos with audio and text translations. To evaluate our models, we report Dynamic Time Warping (DTW) and Probability of Correct Keypoints (PCK) scores. We find that combining prosody and text as input, along with incorporating facial action unit prediction as an additional task, outperforms previous models in both DTW and PCK scores. We also discuss the challenges and limitations of speech-to-sign pose generation models to encourage future research in this domain. We release our models, results and code to foster reproducibility and encourage future research1.

Abstract

A central question in the psycholinguistic study of multilingualism is how syntax is shared across languages. We implement a model to investigate whether error-based implicit learning can provide an account of cross-language structural priming. The model is based on the Dual-path model of
sentence-production (Chang, 2002). We implement our model using the Bilingual version of Dual-path (Tsoukala, Frank, & Broersma, 2017). We answer two main questions: (1) Can structural priming of active and passive constructions occur between English and Spanish in a bilingual version of the Dual-
path model? (2) Does cross-language priming differ quantitatively from within-language priming in this model? Our results show that cross-language priming does occur in the model. This finding adds to the viability of implicit learning as an account of structural priming in general and cross-language
structural priming specifically. Furthermore, we find that the within-language priming effect is somewhat stronger than the cross-language effect. In the context of mixed results from
behavioral studies, we interpret the latter finding as an indication that the difference between cross-language and within-
language priming is small and difficult to detect statistically.

Abstract

The previous literature has suggested that the hand movement in co-speech gestures and signs consists of a series of phases with qualitatively different dynamic characteristics. In this paper, we propose a syntagmatic rule system for movement phases that applies to both co-speech gestures and signs. Descriptive criteria for the rule system were developed for the analysis video-recorded continuous production of signs and gesture. It involves segmenting a stream of body movement into phases and identifying different phase types. Two human coders used the criteria to analyze signs and cospeech gestures that are produced in natural discourse. It was found that the criteria yielded good inter-coder reliability. These criteria can be used for the technology of automatic recognition of signs and co-speech gestures in order to segment continuous production and identify the potentially meaningbearing phase.

Abstract

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

Abstract

Interpreting the meaning of co-speech gesture often involves
identifying a gesture’s ‘lexical affiliate’, the word or phrase to
which it most closely relates (Schegloff 1984). Though there is
work within gesture studies that resists this simplex mapping of
meaning from speech to gesture (e.g. de Ruiter 2000; Kendon
2014; Parrill 2008), including an evolving body of literature on
recurrent gesture and gesture families (e.g. Fricke et al. 2014; Müller 2017), it is still the lexical affiliate model that is most ap-
parent in formal linguistic models of multimodal meaning(e.g.
Alahverdzhieva et al. 2017; Lascarides and Stone 2009; Puste-
jovsky and Krishnaswamy 2021; Schlenker 2020). In this work,
I argue that the lexical affiliate should be carefully reconsidered
in the further development of such models.
In place of the lexical affiliate, I suggest a further shift
toward a frame-based, action schematic approach to gestural
meaning in line with that proposed in, for example, Parrill and
Sweetser (2004) and Müller (2017). To demonstrate the utility
of this approach I present three types of compositional gesture
sequences which I call spatial contrast, spatial embedding, and
cooperative abstract deixis. All three rely on gestural context,
rather than gesture-speech alignment, to convey interactive (i.e.
pragmatic) meaning. The centrality of gestural context to ges-
ture meaning in these examples demonstrates the necessity of
developing a model of gestural meaning independent of its in-
tegration with speech.

Abstract

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

Abstract

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

Large language models that exhibit instruction-following behaviour represent one of the biggest recent upheavals in conversational interfaces, a trend in large part fuelled by the release of OpenAI's ChatGPT, a proprietary large language model for text generation fine-tuned through reinforcement learning from human feedback (LLM+RLHF). We review the risks of relying on proprietary software and survey the first crop of open-source projects of comparable architecture and functionality. The main contribution of this paper is to show that openness is differentiated, and to offer scientific documentation of degrees of openness in this fast-moving field. We evaluate projects in terms of openness of code, training data, model weights, RLHF data, licensing, scientific documentation, and access methods. We find that while there is a fast-growing list of projects billing themselves as 'open source', many inherit undocumented data of dubious legality, few share the all-important instruction-tuning (a key site where human labour is involved), and careful scientific documentation is exceedingly rare. Degrees of openness are relevant to fairness and accountability at all points, from data collection and curation to model architecture, and from training and fine-tuning to release and deployment.

Abstract

Speech recognition systems are a key intermediary in voice-driven human-computer interaction. Although speech recognition works well for pristine monologic audio, real-life use cases in open-ended interactive settings still present many challenges. We argue that timing is mission-critical for dialogue systems, and evaluate 5 major commercial ASR systems for their conversational and multilingual support. We find that word error rates for natural conversational data in 6 languages remain abysmal, and that overlap remains a key challenge (study 1). This impacts especially the recognition of conversational words (study 2), and in turn has dire consequences for downstream intent recognition (study 3). Our findings help to evaluate the current state of conversational ASR, contribute towards multidimensional error analysis and evaluation, and identify phenomena that need most attention on the way to build robust interactive speech technologies.

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

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

Many studies investigating the temporal alignment of co-speech
gestures to acoustic units in the speech signal find a close
coupling of the gestural landmarks and pitch accents or the
stressed syllable of pitch-accented words. In English, a pitch
accent is anchored in the lexically stressed syllable. Hence, it is
unclear whether it is the lexical phonological dimension of
stress, or the phrase-level prominence that determines the
details of speech-gesture synchronization. This paper explores
the relation between gestural phase transitions and accentual F0
peaks in Stockholm Swedish, which exhibits a lexical pitch
accent distinction. When produced with phrase-level
prominence, there are three different configurations of
lexicality of F0 peaks and the status of the syllable it is aligned
with. Through analyzing the alignment of the different F0 peaks
with gestural onsets in spontaneous dyadic conversations, we
aim to contribute to our understanding of the role of lexical
prosodic phonology in the co-production of speech and gesture.
The results, though limited by a small dataset, still suggest
differences between the three types of peaks concerning which
types of gesture phase onsets they tend to align with, and how
well these landmarks align with each other, although these
differences did not reach significance.

Abstract

Phonetic convergence—i.e., adapting one’s speech
towards that of an interlocutor—has been shown
to occur in human-human conversations as well as
human-machine interactions. Here, we investigate
the hypothesis that human-to-robot convergence is
influenced by the human’s perception of the robot
and by the conversation’s topic. We conducted a
within-subjects experiment in which 33 participants
interacted with two robots differing in their eye gaze
behavior—one looked constantly at the participant;
the other produced gaze aversions, similarly to a
human’s behavior. Additionally, the robot asked
questions with increasing intimacy levels.
We observed that the speakers tended to converge
on F0 to the robots. However, this convergence
to the robots was not modulated by how the
speakers perceived them or by the topic’s intimacy.
Interestingly, speakers produced lower F0 means
when talking about more intimate topics. We
discuss these findings in terms of current theories of
conversational convergence.

Abstract

Japanese, British English and American English listeners were presented with spoken words in their native language, and asked to mark on a written transcript of each word the first natural division point in the word. The results showed clear and strong patterns of consensus, indicating that listeners have available to them conscious representations of within-word structure. Orthography did not play a strongly deciding role in the results. The patterns of response were at variance with results from on-line studies of speech segmentation, suggesting that the present task taps not those representations used in on-line listening, but levels of representation which may involve much richer knowledge of word-internal structure.

Abstract

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

Abstract

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

Children’s ability to share attention with another social partner (i.e., joint attention) has been found to support language development. Despite the large amount of research examining the effects of joint attention on language in hearing population, little is known about how deaf children learning sign languages achieve joint attention with their caregivers during natural social interaction and how caregivers provide and scaffold learning opportunities for their children. The present study investigates the properties and timing of joint attention surrounding familiar and novel naming events and their relationship to children’s vocabulary. Naturalistic play sessions of caretaker-child-dyads using American Sign Language were analyzed in regards to naming events of either familiar or novel object labeling events and the surrounding joint attention events. We observed that most naming events took place in the context of a successful joint attention event and that sign familiarity was related to the timing of naming events within the joint attention events. Our results suggest that caregivers are highly sensitive to their child’s visual attention in interactions and modulate joint attention differently in the context of naming events of familiar vs. novel object labels.

Abstract

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

Abstract

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

Abstract

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

Abstract

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.