Publications

Abstract

Corpus linguistics and language documentation are usually considered separate subdisciplines within linguistics, having developed from different traditions and often operating on different scales, but the authors will suggest that there are commonalities to the two: both aim to represent language use in a community, and both are concerned with managing digital data. The authors propose that the development of the Australian National Corpus (AusNC) be guided by the experience of language documentation in the management of multimodal digital data and its annotation, and in ethical issues pertaining to making the data accessible. This would allow an AusNC that is distributed, multimodal, and multilingual, with holdings of text, audio, and video data distributed across multiple institutions; and including Indigenous, sign, and migrant community languages. An audit of language material held by Australian institutions and individuals is necessary to gauge the diversity and volume of possible content, and to inform common technical standards.

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

-* 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

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

Abstract

Word count estimation (WCE) from audio recordings has a number of applications, including quantifying the amount of speech that language-learning infants hear in their natural environments, as captured by daylong recordings made with devices worn by infants. To be applicable in a wide range of scenarios and also low-resource domains, WCE tools should be extremely robust against varying signal conditions and require minimal access to labeled training data in the target domain. For this purpose, earlier work has used automatic syllabification of speech, followed by a least-squares-mapping of syllables to word counts. This paper compares a number of previously proposed syllabifiers in the WCE task, including a supervised bi-directional long short-term memory (BLSTM) network that is trained on a language for which high quality syllable annotations are available (a “high resource language”), and reports how the alternative methods compare on different languages and signal conditions. We also explore additive noise and varying-channel data augmentation strategies for BLSTM training, and show how they improve performance in both matching and mismatching languages. Intriguingly, we also find that even though the BLSTM works on languages beyond its training data, the unsupervised algorithms can still outperform it in challenging signal conditions on novel languages.

Abstract

LEXUS and ViCoS: from lexicon to conceptual spaces LEXUS is a web-based lexicon tool and the knowledge space software ViCoS is an extension of LEXUS, allowing users to create relations between objects in and across lexica. LEXUS and ViCoS are part of the Language Archiving Technology software, developed at the MPI for Psycholinguistics to archive and enrich linguistic resources collected in the framework of language documentation projects. LEXUS is of primary interest for language documentation, offering the possibility to not just create a digital dictionary, but additionally it allows the creation of multi-media encyclopedic lexica. ViCoS provides an interface between the lexical space and the ontological space. Its approach permits users to model a world of concepts and their interrelations based on categorization patterns made by the speech community. We describe the LEXUS and ViCoS functionalities using three cases from DoBeS language documentation projects: (1) Marquesan The Marquesan lexicon was initially created in Toolbox and imported into LEXUS using the Toolbox import functionality. The lexicon is enriched with multi-media to illustrate the meaning of the words in its cultural environment. Members of the speech community consider words as keys to access and describe relevant parts of their life and traditions. Their understanding of words is best described by the various associations they evoke rather than in terms of any formal theory of meaning. Using ViCoS a knowledge space of related concepts is being created. (2) Kola-Sámi Two lexica are being created in LEXUS: RuSaDic lexicon is a Russian-Kildin wordlist in which the entries are of relative limited structure and content. SaRuDiC is a more complex structured lexicon with much richer content, including multi-media fragments and derivations. Using ViCoS we have created a connection between the two lexica, so that speakers who are familiair with Russian and wish to revitalize their Kildin can enter the lexicon through the RuSaDic and from there approach the informative SaRuDic. Similary we will create relations from the two lexica to external open databases, like e.g. Álgu. (3) Beaver A speaker database including kinship relations has been created and the database has been imported into LEXUS. In the LEXUS views the relations for individual speakers are being displayed. Using ViCoS the relational information from the database will be extracted to form a kisnhip relation space with specific relation types, like e.g 'mother-of'. The whole set of relations from the database can be displayed in one ViCoS relation window, and zoom functionality is available.

Abstract

Thematic roles such as Agent and Instrument have a long-standing place in theories of event representation. Nonetheless, the structure of these categories has been difficult to determine. We investigated how instrumental events, such as someone slicing bread with a knife, are categorized in English. Speakers described a variety of typical and atypical instrumental events, and we determined the similarity structure of their descriptions using correspondence analysis. We found that events where the instrument is an extension of an intentional agent were most likely to elicit similar language, highlighting the importance of agency in structuring instrumental categories.

Abstract

The annual conference of the European Second Language Association provides an opportunity for the presentation of second language research with a genuinely European flavour. The theoretical perspectives adopted are wide-ranging and may fall within traditions overlooked elsewhere. Moreover, the studies presented are largely multi-lingual and cross-cultural, as befits the make-up of modern-day Europe. At the same time, the work demonstrates sophisticated awareness of scholarly insights from around the world. The EUROSLA yearbook presents a selection each year of the very best research from the annual conference. Submissions are reviewed and professionally edited, and only those of the highest quality are selected. Contributions are in English.

Abstract

For almost two decades, the poor performance observed with the so-called Director task has been interpreted as evidence of limited use of Theory of Mind in communication. Here we propose a probabilistic model of common ground in referential communication that derives three inferences from an utterance: what the speaker is talking about in a visual context, what she knows about the context, and what referential expressions she prefers. We tested our model by comparing its inferences with those made by human participants and found that it closely mirrors their judgments, whereas an alternative model compromising the hearer’s expectations of cooperativeness and efficiency reveals a worse fit to the human data. Rather than assuming that common ground is fixed in a given exchange and may or may not constrain reference resolution, we show how common ground can be inferred as part of the process of reference assignment.

Abstract

In this paper, I will argue that although the study of multimodal interaction offers exciting new prospects for Human Computer Interaction and human-human communication research, language is the primary form of communication, even in multimodal systems. I will support this claim with theoretical and empirical arguments, mainly drawn from human-human communication research, and will discuss the implications for multimodal communication research and Human-Computer Interaction.

Abstract

While there are many studies on information retrieval models using full-text, there are presently no comparison studies of full-text retrieval vs. retrieval only over the titles of documents. On the one hand, the full-text of documents like scientific papers is not always available due to, e.g., copyright policies of academic publishers. On the other hand, conducting a search based on titles alone has strong limitations. Titles are short and therefore may not contain enough information to yield satisfactory search results. In this paper, we compare different retrieval models regarding their search performance on the full-text vs. only titles of documents. We use different datasets, including the three digital library datasets: EconBiz, IREON, and PubMed. The results show that it is possible to build effective title-based retrieval models that provide competitive results comparable to full-text retrieval. The difference between the average evaluation results of the best title-based retrieval models is only 3% less than those of the best full-text-based retrieval models.

Abstract

Most of the study of basic emotion expressions has focused on facial expressions and little work has been done to specifically investigate happiness, the only positive of the basic emotions (Ekman & Friesen, 1971). However, a theoretical suggestion has been made that happiness could be broken down into discrete positive emotions, which each fulfil the criteria of basic emotions, and that these would be expressed vocally (Ekman, 1992). To empirically test this hypothesis, 20 participants categorised 80 paralinguistic sounds using the labels achievement, amusement, contentment, pleasure and relief. The results suggest that achievement, amusement and relief are perceived as distinct categories, which subjects accurately identify. In contrast, the categories of contentment and pleasure were systematically confused with other responses, although performance was still well above chance levels. These findings are initial evidence that the positive emotions engage distinct vocal expressions and may be considered to be distinct emotion categories.

Abstract

Emotional signals allow for the sharing of important information with conspecifics, for example to warn them of danger. Humans use a range of different cues to communicate to others how they feel, including facial, vocal, and gestural signals. Although much is known about facial expressions of emotion, less research has focused on affect in the voice. We compare British listeners to individuals from remote Namibian villages who have had no exposure to Western culture, and examine recognition of non-verbal emotional vocalizations, such as screams and laughs. We show that a number of emotions can be universally recognized from non-verbal vocal signals. In addition we demonstrate the specificity of this pattern, with a set of additional emotions only recognized within, but not across these cultural groups. Our findings indicate that a small set of primarily negative emotions have evolved signals across several modalities, while most positive emotions are communicated with culture-specific signals.

Abstract

Fine-Tracker is a speech-based model of human speech
recognition. While previous work has shown that Fine-Tracker
is successful at modelling aspects of human spoken-word
recognition, its speech recognition performance is not
comparable to that of human performance, possibly due to
suboptimal intermediate articulatory feature (AF)
representations. This study investigates the effect of improved
AF representations, obtained using a state-of-the-art deep
convolutional network, on Fine-Tracker’s simulation and
recognition performance: Although the improved AF quality
resulted in improved speech recognition; it, surprisingly, did
not lead to an improvement in Fine-Tracker’s simulation power.

Abstract

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

Abstract

In this paper, we investigate the ability of SpeM, our recognition system based on the combination of an automatic phone recogniser and a wordsearch module, to determine as early as possible during the word recognition process whether a word is likely to be recognised correctly (this we refer to as ‘on-line’ early word recognition). We present two measures that can be used to predict whether a word is correctly recognised: the Bayesian word activation and the amount of available (acoustic) information for a word. SpeM was tested on 1,463 polysyllabic words in 885 continuous speech utterances. The investigated predictors indicated that a word activation that is 1) high (but not too high) and 2) based on more phones is more reliable to predict the correctness of a word than a similarly high value based on a small number of phones or a lower value of the word activation.

Abstract

A stretch of speech is often consistent with multiple words, e.g., the sequence /hæm/ is consistent with ‘ham’ but also with the first syllable of ‘hamster’, resulting in temporary ambiguity. However, to what degree does this lexical embedding occur? Analyses on two corpora of spoken Dutch showed that 11.9%-19.5% of polysyllabic word tokens have word-initial embedding, while 4.1%-7.5% of monosyllabic word tokens can appear word-initially embedded. This is much lower than suggested by an analysis of a large dictionary of Dutch. Speech processing thus appears to be simpler than one might expect on the basis of statistics on a dictionary.

Abstract

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

Abstract

Evidence that listeners use durational cues to help resolve temporarily ambiguous speech input has accumulated over the past few years. In this paper, we investigate whether durational cues are also beneficial for word recognition in a computational model of spoken-word recognition. Two sets of simulations were carried out using the acoustic signal as input. The simulations showed that the computational model, like humans, takes benefit from durational cues during word recognition, and uses these to disambiguate the speech signal. These results thus provide support for the theory that durational cues play a role in spoken-word recognition.

Abstract

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

Abstract

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

Abstract

The study endeavors a detailed and systematic classification of linguistic simultaneity expressions. Further, it aims at a well described survey of how simultaneity is expressed by native speakers in their own language. On the basis of real production data the book answers the questions of how native speakers express temporal simultaneity in general, and how learners at different levels of proficiency deal with this situation under experimental test conditions. Furthermore, the results of this study shed new light on our understanding of aspect in general, and on its acquisition by adult learners.

Abstract

This paper addresses the role of the adverb in Dutch direct object scrambling constructions. We report four experiments in which we investigate whether the structural position and the scope sensitivity of the adverb affect acceptability judgments of scrambling constructions and native speakers' tendency to scramble definite objects. We conclude that the type of adverb plays a key role in Dutch word ordering preferences.

Abstract

We tested whether statistical averageness (SA) at the level of the individual speaker could predict a speaker’s intelligibility. 28 female and 21 male speakers of Dutch were recorded producing 336 sentences,
each containing two target nouns. Recordings were compared to those of all other same-sex speakers using dynamic time warping (DTW). For each sentence, the DTW distance constituted a metric
of phonetic distance from one speaker to all other speakers. SA comprised the average of these distances. Later, the same participants performed a word recognition task on the target nouns in the same sentences, under three degraded listening conditions. In all three conditions, accuracy increased with SA. This held even when participants listened to their own utterances. These findings suggest that listeners process speech with respect to the statistical
properties of the language spoken in their community, rather than using their own speech as a reference

Abstract

This paper presents a study on the reduction of word-final [t]s in conversational standard Dutch. Based on a large amount of tokens annotated on the segmental level, we show that the bigram frequency and the segmental context are the main predictors for the absence of [t]s. In a second study, we present an analysis of the detailed acoustic properties of word-final [t]s and we show that bigram frequency and context also play a role on the subsegmental level. This paper extends research on the realization of /t/ in spontaneous speech and shows the importance of incorporating sub-segmental properties in models of speech.

Abstract

Previous studies have indicated that vocal and facial expressions of the ‘basic’ emotions share aspects of processing. Thus amygdala damage compromises the perception of fear and anger from the face and from the voice. In the current study we tested the hypothesis that there exist positive basic emotions, expressed mainly in the voice (Ekman, 1992). Vocal stimuli were produced to express the specific positive emotions of amusement, achievement, pleasure, contentment and relief.

Abstract

Like every other social sphere, science is influenced by individual characteristics of researchers. However, for investigations on scientific networks, only little data about the social background of researchers, e.g. social origin, gender, affiliation etc., is available.
This paper introduces ”Take it personally - TIP”, a conceptual model and library currently under development, which aims to support the
semantic enrichment of publication databases with semantically related background information which resides elsewhere in the (semantic) web, such as Wikidata.
The supplementary information enriches the original information in the publication databases and thus facilitates the creation of complex scientific knowledge graphs. Such enrichment helps to improve the scientometric analysis of scientific publications as they can also take social backgrounds of researchers into account and to understand social structure in research communities.

Abstract

Feedforward deep convolutional neural networks (DCNNs) are matching and even surpassing human performance on object recognition. This performance suggests that activation of a loose collection of image
features could support the recognition of natural object categories, without dedicated systems to solve specific visual subtasks. Recent findings in humans however, suggest that while feedforward activity may suffice for
sparse scenes with isolated objects, additional visual operations ('routines') that aid the recognition process (e.g. segmentation or grouping) are needed for more complex scenes. Linking human visual processing to
performance of DCNNs with increasing depth, we here explored if, how, and when object information is differentiated from the backgrounds they appear on. To this end, we controlled the information in both objects
and backgrounds, as well as the relationship between them by adding noise, manipulating background congruence and systematically occluding parts of the image. Results indicated less distinction between object- and background features for more shallow networks. For those networks, we observed a benefit of training on segmented objects (as compared to unsegmented objects). Overall, deeper networks trained on natural
(unsegmented) scenes seem to perform implicit 'segmentation' of the objects from their background, possibly by improved selection of relevant features.

Abstract

When we communicate, we communicate in a certain context, and this context shapes our utterances. Natural languages are context-bound and deixis 'concerns the ways in which languages encode or grammaticalise features of the context of utterance or speech event, and thus also concerns ways in which the interpretation of utterances depends on the analysis of that context of utterance' (Stephen Levinson). The systems of deixis and demonstratives in the Oceanic languages represented in the contributions to this volume illustrate the fascinating complexity of spatial reference in these languages. Some of the studies presented here highlight social aspects of deictic reference illustrating de Leon's point that 'reference is a collaborative task' . It is hoped that this anthology will contribute to a better understanding of this area and provoke further studies in this extremely interesting, though still rather underdeveloped, research area.

Abstract

This volume deals with the children’s socialization on the Trobriands. After a survey of ethnographic studies on childhood, the book zooms in on indigenous ideas of conception and birth-giving, the children’s early development, their integration into playgroups, their games and their education within their `own little community’ until they reach the age of seven years. During this time children enjoy much autonomy and independence. Attempts of parental education are confined to a minimum. However, parents use subtle means to raise their children. Educational ideologies are manifest in narratives and in speeches addressed to children. They provide guidelines for their integration into the Trobrianders’ “balanced society” which is characterized by cooperation and competition. It does not allow individual accumulation of wealth – surplus property gained has to be redistributed – but it values the fame acquired by individuals in competitive rituals. Fame is not regarded as threatening the balance of their society.

Abstract

Language in Cognition argues that language is based on the human construal of reality. Humans refer to and quantify over virtual entities with the same ease as they do over actual entities: the natural ontology of language, the author argues, must therefore comprise both actual and virtual entities and situations. He reformulates speech act theory, suggesting that the primary function of language is less the transfer of information than the establishing of socially binding commitments or appeals based on the proposition expressed. This leads him first to a new analysis of the systems and structures of cognitive language machinery and their ecological embedding, and finally to a reformulation of the notion of meaning, in which sentence meaning is distinguished from lexical meaning and the vagaries and multifarious applications of lexical meanings may be explained and understood. This is the first of a two-volume foundational study of language, published under the title, Language from Within. Pieter Seuren discusses and analyses such apparently diverse issues as the ontology underlying the semantics of language, speech act theory, intensionality phenomena, the machinery and ecology of language, sentential and lexical meaning, the natural logic of language and cognition, and the intrinsically context-sensitive nature of language - and shows them to be intimately linked. Throughout his ambitious enterprise, he maintains a constant dialogue with established views, reflecting on their development from Ancient Greece to the present. The resulting synthesis concerns central aspects of research and theory in linguistics, philosophy, and cognitive science.

Abstract

The present paper is part of a large research programme investigating the nature and properties of the predicate logic inherent in natural language. The general hypothesis is that natural speakers start off with a basic-natural logic, based on natural cognitive functions, including the basic-natural way of dealing with plural objects. As culture spreads, functional pressure leads to greater generalization and mathematical correctness, yielding ever more refined systems until the apogee of standard modern predicate logic. Four systems of predicate calculus are considered: Basic-Natural Predicate Calculus (BNPC), Aritsotelian-Abelardian Predicate Calculus (AAPC), Aritsotelian-Boethian Predicate Calculus (ABPC), also known as the classic Square of Opposition, and Standard Modern Predicate Calculus (SMPC). (ABPC is logically faulty owing to its Undue Existential Import (UEI), but that fault is repaired by the addition of a presuppositional component to the logic.) All four systems are checked against seven natural logical intuitions. It appears that BNPC scores best (five out of seven), followed by ABPC (three out of seven). AAPC and SMPC finish ex aequo with two out of seven.

Abstract

This book presents a detailed formal machinery for the conversion of the Semantic Analyses (SAs) of sentences into surface structures of English, French, German, Dutch, and to some extent Turkish. The SAs are propositional structures consisting of a predicate and one, two or three argument terms, some of which can themselves be propositional structures. The surface structures are specified up to, but not including, the morphology. The book is thus an implementation of the programme formulated first by Albert Sechehaye (1870-1946) and then, independently, by James McCawley (1938-1999) in the school of Generative Semantics. It is the first, and so far the only formally precise and empirically motivated machinery in existence converting meaning representations into sentences of natural languages.

Abstract

The results of an eye-tracking experiment are presented in which Dutch listeners' eye movements were monitored as they heard sentences and saw four pictured objects. Participants were instructed to click on the object mentioned in the sentence. In the critical sentences, a stop-initial target (e.g., "pot") was preceded by an [s], thus causing ambiguity regarding whether the sentence refers to a stop-initial or a cluster-initial word (e.g., "spot"). Participants made fewer fixations to the target pictures when the stop and the preceding [s] were cross-spliced from the cluster-initial word than when they were spliced from a different token of the sentence containing the stop-initial word. Acoustic analyses showed that the two versions differed in various measures, but only one of these - the duration of the [s] - correlated with the perceptual effect. Thus, in this context, the [s] duration information is an important factor guiding word recognition.

Abstract

ndividual talkers may use various strategies to enrich their speech while speaking in noise (i.e., Lombard speech) to improve their intelligibility. The resulting acoustic-phonetic changes in Lombard speech vary amongst different speakers, but it is unclear what causes these talker differences, and what impact these differences have on intelligibility. This study investigates the potential role of articulatory control in talkers’ Lombard speech enrichment success. Seventy-eight speakers read out sentences in both their habitual style and in a condition where they were instructed to speak clearly while hearing loud speech-shaped noise. A diadochokinetic (DDK) speech task that requires speakers to repetitively produce word or non-word sequences as accurately and as rapidly as possible, was used to quantify their articulatory control. Individuals’ predicted intelligibility in both speaking styles (presented at -5 dB SNR) was measured using an acoustic glimpse-based metric: the High-Energy Glimpse Proportion (HEGP). Speakers’ HEGP scores show a clear effect of speaking condition (better HEGP scores in the Lombard than habitual condition), but no simple effect of articulatory control on HEGP, nor an interaction between speaking condition and articulatory control. This indicates that individuals’ speech enrichment success as measured by the HEGP metric was not predicted by DDK performance.

Abstract

E-Prime® is the leading software suite by Psychology Software Tools for designing and running Psychology lab experiments. The E-Primer is the perfect accompanying guide: It provides all the necessary knowledge to make E-Prime accessible to everyone. You can learn the tools of Psychological science by following the E-Primer through a series of entertaining, step-by-step recipes that recreate classic experiments. The updated E-Primer expands its proven combination of simple explanations, interesting tutorials and fun exercises, and makes even the novice student quickly confident to create their dream experiment.

Abstract

We report an individual with music-odor synaesthesia who experiences automatic and vivid odor sensations when she hears music. S’s odor associations were recorded on two days, and compared with those of two control participants. Overall, S produced longer descriptions, and her associations were of multiple odors at once, in comparison to controls who typically reported a single odor. Although odor associations were qualitatively different between S and controls, ratings of the consistency of their descriptions did not differ. This demonstrates that crossmodal associations between music and odor exist in non-synaesthetes too. We also found that S is better at discriminating between odors than control participants, and is more likely to experience emotion, memories and evaluations triggered by odors, demonstrating the broader impact of her synaesthesia.

Abstract

Metaphor allows us to think and talk about one thing in terms of another, ratcheting up our cognitive and expressive capacity. It gives us concrete terms for abstract phenomena, for example, ideas become things we can grasp or let go of. Perceptual experience—characterised as physical and relatively concrete—should be an ideal source domain in metaphor, and a less likely target. But is this the case across diverse languages? And are some sensory modalities perhaps more concrete than others? This volume presents critical new data on perception metaphors from over 40 languages, including many which are under-studied. Aside from the wealth of data from diverse languages—modern and historical; spoken and signed—a variety of methods (e.g., natural language corpora, experimental) and theoretical approaches are brought together. This collection highlights how perception metaphor can offer both a bedrock of common experience and a source of continuing innovation in human communication

Abstract

The problem of identifying and correcting confusibles, i.e. context-sensitive spelling errors, in text is typically tackled using specifically trained machine learning classifiers. For each different set of confusibles, a specific classifier is trained and tuned. In this research, we investigate a more generic approach to context-sensitive confusible correction. Instead of using specific classifiers, we use one generic classifier based on a language model. This measures the likelihood of sentences with different possible solutions of a confusible in place. The advantage of this approach is that all confusible sets are handled by a single model. Preliminary results show that the performance of the generic classifier approach is only slightly worse that that of the specific classifier approach

Abstract

In the context of confusible disambiguation (spelling correction that requires context), the synchronous back-off strategy combined with traditional n-gram language models performs well. However, when alternatives consist of a different number of tokens, this classification technique cannot be applied directly, because the computation of the probabilities is skewed. Previous work already showed that probabilities based on different order n-grams should not be compared directly. In this article, we propose new probability metrics in which the size of the n is varied according to the number of tokens of the confusible alternative. This requires access to n-grams of variable length. Results show that the synchronous back-off method is extremely robust. We discuss the use of suffix trees as a technique to store variable length n-gram information efficiently.

Abstract

This paper presents a quantitative analysis of the
turn-taking mechanism evidenced in 93 telephone
dialogues that were taken from the 9-million-word
Spoken Dutch Corpus. While the first part of the paper
focuses on the temporal phenomena of turn taking, such
as durations of pauses and overlaps of turns in the
dialogues, the second part explores the discoursefunctional
aspects of utterances in a subset of 8
dialogues that were annotated especially for this
purpose. The results show that speakers adapt their turntaking
behaviour to the interlocutor’s behaviour.
Furthermore, the results indicate that male-male dialogs
show a higher proportion of overlapping turns than
female-female dialogues.

Abstract

Sequences of reaction times (RT) produced by participants in an experiment are not only influenced by the stimuli, but by many other factors as well, including fatigue, attention, experience, IQ, handedness, etc. These confounding factors result in longterm effects (such as a participant’s overall reaction capability) and in short- and medium-time fluctuations in RTs (often referred to as ‘local speed effects’). Because stimuli are usually presented in a random sequence different for each participant, local speed effects affect the underlying ‘true’ RTs of specific trials in different ways across participants. To be able to focus statistical analysis on the effects of the cognitive process under study, it is necessary to reduce the effect of confounding factors as much as possible. In this paper we propose and compare techniques and criteria for doing so, with focus on reducing (‘filtering’) the local speed effects. We show that filtering matters substantially for the significance analyses of predictors in linear mixed effect regression models. The performance of filtering is assessed by the average between-participant correlation between filtered RT sequences and by Akaike’s Information Criterion, an important measure of the goodness-of-fit of linear mixed effect regression models.

Abstract

The neural processing of speech leads to specific patterns in the brain which can be measured as, e.g., EEG signals. When properly aligned with the speech input and averaged over many tokens, the Event Related Potential (ERP) signal is able to differentiate specific contrasts between speech signals. Well-known effects relate to the difference between expected and unexpected words, in particular in the N400, while effects in N100 and P200 are related to attention and acoustic onset effects. Most EEG studies deal with the amplitude of EEG signals over time, sidestepping the effect of phase and phase synchronization. This paper investigates the relation between phase in the EEG signals measured in an auditory lexical decision task by Dutch participants listening to full and reduced English word forms. We show that phase synchronization takes place across stimulus conditions, and that the so-called circular variance is narrowly related to the type of contrast between stimuli.

Abstract

On the basis of two-speaker spontaneous conversations, it is shown that the distributions of both pauses and speech-overlaps of telephone and faceto-face dialogues have different statistical properties. Pauses in a face-to-face
dialogue last up to 4 times longer than pauses in telephone conversations in functionally comparable conditions. There is a high correlation (0.88 or larger) between the average pause duration for the two speakers across face-to-face
dialogues and telephone dialogues. The data provided form a first quantitative analysis of the complex turn-taking mechanism evidenced in the dialogues available in the 9-million-word Spoken Dutch Corpus.

Abstract

The recent advent of deep learning techniques in speech tech-nology and in particular in automatic speech recognition hasyielded substantial performance improvements. This suggeststhat deep neural networks (DNNs) are able to capture structurein speech data that older methods for acoustic modeling, suchas Gaussian Mixture Models and shallow neural networks failto uncover. In image recognition it is possible to link repre-sentations on the first couple of layers in DNNs to structuralproperties of images, and to representations on early layers inthe visual cortex. This raises the question whether it is possi-ble to accomplish a similar feat with representations on DNNlayers when processing speech input. In this paper we presentthree different experiments in which we attempt to untanglehow DNNs encode speech signals, and to relate these repre-sentations to phonetic knowledge, with the aim to advance con-ventional phonetic concepts and to choose the topology of aDNNs more efficiently. Two experiments investigate represen-tations formed by auto-encoders. A third experiment investi-gates representations on convolutional layers that treat speechspectrograms as if they were images. The results lay the basisfor future experiments with recursive networks.

Abstract

In everyday life, people see, describe and remember motion events. We tested whether the type of motion event information (path or manner) encoded in speech and gesture predicts which information is remembered and if this varies across speakers of typologically different languages. We focus on intransitive motion events (e.g., a woman running to a tree) that are described differently in speech and co-speech gesture across languages, based on how these languages typologically encode manner and path information (Kita & Özyürek, 2003; Talmy, 1985). Speakers of Dutch (n = 19) and Turkish (n = 22) watched and described motion events. With a surprise (i.e. unexpected) recognition memory task, memory for manner and path components of these events was measured. Neither Dutch nor Turkish speakers’ memory for manner went above chance levels. However, we found a positive relation between path speech and path change detection: participants who described the path during encoding were more accurate at detecting changes to the path of an event during the memory task. In addition, the relation between path speech and path memory changed with native language: for Dutch speakers encoding path in speech was related to improved path memory, but for Turkish speakers no such relation existed. For both languages, co-speech gesture did not predict memory speakers. We discuss the implications of these findings for our understanding of the relations between speech, gesture, type of encoding in language and memory.

Abstract

We estimate lexical Concreteness for millions of words across 77 languages. Using a simple regression framework, we combine vector-based models of lexical semantics with experimental norms of Concreteness in English and Dutch. By applying techniques to align vector-based semantics across distinct languages, we compute and release Concreteness estimates at scale in numerous languages for which experimental norms are not currently available. This paper lays out the technique and its efficacy. Although this is a difficult dataset to evaluate immediately, Concreteness estimates computed from English correlate with Dutch experimental norms at $\rho$ = .75 in the vocabulary at large, increasing to $\rho$ = .8 among Nouns. Our predictions also recapitulate attested relationships with word frequency. The approach we describe can be readily applied to numerous lexical measures beyond Concreteness

Abstract

Do all languages convey semantic knowledge in the same way? If language simply mirrors the structure of the world, the answer should be a qualified “yes”. If, however, languages impose structure as much as reflecting it, then even ostensibly the “same” word in different languages may mean quite different things. We provide a first pass at a large-scale quantification of cross-linguistic semantic alignment of approximately 1000 meanings in 55 languages. We find that the translation equivalents in some domains (e.g., Time, Quantity, and Kinship) exhibit high alignment across languages while the structure of other domains (e.g., Politics, Food, Emotions, and Animals) exhibits substantial cross-linguistic variability. Our measure of semantic alignment correlates with known phylogenetic distances between languages: more phylogenetically distant languages have less semantic alignment. We also find semantic alignment to correlate with cultural distances between societies speaking the languages, suggesting a rich co-adaptation of language and culture even in domains of experience that appear most constrained by the natural world

Abstract

The present study shows that [t] consonants are affected by probabilistic factors in a syllable-timed language as French, and in spontaneous as well as in journalistic speech. Study 1 showed a word bigram frequency effect in spontaneous French, but its exact nature depended on the corpus on which the probabilistic measures were based. Study 2 investigated journalistic speech and showed an effect of the joint frequency of the test word and its following word. We discuss the possibility that these probabilistic effects are due to the speaker’s planning of upcoming words, and to the speaker’s adaptation to the listener’s needs.

Abstract

In situated communication, reference to an entity in the shared visual context can be established using eitheranexpression that conveys precise (minimally specified) or redundant (over-specified) information. There is, however, along-lasting debate in psycholinguistics concerningwhether the latter hinders referential processing. We present evidence from an eyetrackingexperiment recordingfixations as well asthe Index of Cognitive Activity –a novel measure of cognitive workload –supporting the view that over-specifications facilitate processing. We further present originalevidence that, above and beyond the effect of specificity,referring expressions thatuniformly reduce referential entropyalso benefitprocessing

Abstract

A dominant hypothesis in empirical research on the evolution of language is the following: the fundamental difference between animal and human communication systems is captured by the distinction between regular and more complex non-regular grammars. Studies reporting successful artificial grammar learning of nested recursive structures and imaging studies of the same have methodological shortcomings since they typically allow explicit problem solving strategies and this has been shown to account for the learning effect in subsequent behavioral studies. The present study overcomes these shortcomings by using subtle violations of agreement structure in a preference classification task. In contrast to the studies conducted so far, we use an implicit learning paradigm, allowing the time needed for both abstraction processes and consolidation to take place. Our results demonstrate robust implicit learning of recursively embedded structures (context-free grammar) and recursive structures with cross-dependencies (context-sensitive grammar) in an artificial grammar learning task spanning 9 days. Keywords: Implicit artificial grammar learning; centre embedded; cross-dependency; implicit learning; context-sensitive grammar; context-free grammar; regular grammar; non-regular grammar

Abstract

The task of automatic playlist continuation is generating a list of recommended tracks that can be added to an existing playlist. By suggesting appropriate tracks, i. e., songs to add to a playlist, a recommender system can increase the user engagement by making playlist creation easier, as well as extending listening beyond the end of current playlist. The ACM Recommender Systems Challenge 2018 focuses on such task. Spotify released a dataset of playlists, which includes a large number of playlists and associated track listings. Given a set of playlists from which a number of tracks have been withheld, the goal is predicting the missing tracks in those playlists. We participated in the challenge as the team Unconscious Bias and, in this paper, we present our approach. We extend adversarial autoencoders to the problem of automatic playlist continuation. We show how multiple input modalities, such as the playlist titles as well as track titles, artists and albums, can be incorporated in the playlist continuation task.

Abstract

This paper describes a new flexible delexicalization method based on glottal excited parametric speech synthesis scheme. The system utilizes inverse filtered glottal flow and all-pole modelling of the vocal tract. The method provides a possibility to retain and manipulate all relevant prosodic features of any kind of speech. Most importantly, the features include voice quality, which has not been properly modeled in earlier delexicalization methods. The functionality of the new method was tested in a prosodic tagging experiment aimed at providing word prominence data for a text-to-speech synthesis system. The experiment confirmed the usefulness of the method and further corroborated earlier evidence that linguistic factors influence the perception of prosodic prominence.

Abstract

A not uncommon assumption in psycholinguistics is that the N400 directly indexes high-level semantic integration, the compositional, word-driven construction of sentence- and discourse-level meaning in some language-relevant unification space. The various discourse- and speaker-dependent modulations of the N400 uncovered by us and others are often taken to support this 'compositional integration' position. In my talk, I will argue that these N400 modulations are probably better interpreted as only indirectly reflecting compositional sense-making. The account that I will advance for these N400 effects is a variant of the classic Kutas and Federmeier (2002, TICS) memory retrieval account in which context effects on the word-elicited N400 are taken to reflect contextual priming of LTM access. It differs from the latter in making more explicit that the contextual cues that prime access to a word's meaning in LTM can range from very simple (e.g., a single concept) to very complex ones (e.g., a structured representation of the current discourse). Furthermore, it incorporates the possibility, suggested by recent N400 findings, that semantic retrieval can also be intensified in response to certain ‘relevance signals’, such as strong value-relevance, or a marked delivery (linguistic focus, uncommon choice of words, etc). In all, the perspective I'll draw is that in the context of discourse-level language processing, N400 effects reflect an 'overlay of technologies', with the construction of discourse-level representations riding on top of more ancient sense-making technology.

Abstract

Listeners require context to understand the casual pronunciation variants of words that are typical of spontaneous speech (Ernestus et al., 2002). The present study reports two auditory lexical decision experiments, investigating listeners' use of semantic contextual information in the comprehension of unreduced and reduced words. We found a strong semantic priming effect for low frequency unreduced words, whereas there was no such effect for reduced words. Word frequency was facilitatory for all words. These results show that semantic context is relevant especially for the comprehension of unreduced words, which is unexpected given the listener driven explanation of reduction in spontaneous speech.

Abstract

Before infants become mature speakers of their native language, they must acquire a robust word-recognition system which allows them to strike the balance between allowing some variation (mood, voice, accent) and recognizing variability that potentially changes meaning (e.g. cat vs hat). The current meta-analysis quantifies how the latter, termed mispronunciation sensitivity, changes over infants’ first three years, testing competing predictions of mainstream language acquisition theories. Our results show that infants were sensitive to mispronunciations, but accepted them as labels for target objects. Interestingly, and in contrast to predictions of mainstream theories, mispronunciation sensitivity was not modulated by infant age, suggesting that a sufficiently flexible understanding of native language phonology is in place at a young age.

Abstract

This study concerns individual differences in speech imitation ability and the role that lexical representations play in imitation. We examined 1) whether imitation of sounds in an unfamiliar language (L0) is related to imitation of sounds in an unfamiliar
non-native accent in the speaker’s native language (L1) and 2) whether it is easier or harder to imitate speech when you know the words to be imitated. Fifty-nine native Dutch speakers imitated words with target vowels in Basque (/a/ and /e/) and Greekaccented
Dutch (/i/ and /u/). Spectral and durational
analyses of the target vowels revealed no relationship between the success of L0 and L1 imitation and no difference in performance between tasks (i.e., L1
imitation was neither aided nor blocked by lexical knowledge about the correct pronunciation). The results suggest instead that the relationship of the vowels to native phonological categories plays a bigger role in imitation

Abstract

This paper investigates the production and perception of epenthetic stops at syllable boundaries in Dutch and compares the experimental data with lexical statistics for Dutch and English. This extends past work on epenthesis in coda position [1]. The current work is particularly informative regarding the question of phonotactic constraints’ influence on parsing of speech variability.

Abstract

This paper presents articulatory data on the production of /l/ in various environments in Dutch, and shows that the direction of movement of the tongue dorsum varies across environments. This makes it impossible to measure tongue position at the peak of the dorsal gesture. We argue for an alternative method in such cases: measurement of position of one articulator at a time point defined by the gesture of another. We present new data measured this way which confirms a previous finding on the articulation of Dutch /l/.

Abstract

Two eye-tracking experiments examined linguistic gender effects in non-native spoken-word recognition. French participants, who knew German well, followed spoken instructions in German to click on pictures on a computer screen (e.g., Wo befindet sich die Perle, “where is the pearl”) while their eye movements were monitored. The name of the target picture was preceded by a gender-marked article in the instructions. When a target and a competitor picture (with phonologically similar names) were of the same gender in both German and French, French participants fixated competitor pictures more than unrelated pictures. However, when target and competitor were of the same gender in German but of different gender in French, early fixations to the competitor picture were reduced. Competitor activation in the non-native language was seemingly constrained by native gender information. German listeners showed no such viewing time difference. The results speak against a form-based account of the linguistic gender effect. They rather support the notion that the effect originates from the grammatical level of language processing.

Abstract

Lexical recognition is typically slower in L2 than in L1. Part of the difficulty comes from a not precise enough processing of L2 phonemes. Consequently, L2 listeners fail to eliminate candidate words that L1 listeners can exclude from competing for recognition. For instance, the inability to distinguish /r/ from /l/ in rocket and locker makes for Japanese listeners both words possible candidates when hearing their onset (e.g., Cutler, Weber, and Otake, 2006). The L2 disadvantage can, however, be dispelled: For L2 listeners, but not L1 listeners, L2 speech from a non-native talker with the same language background is known to be as intelligible as L2 speech from a native talker (e.g., Bent and Bradlow, 2003). A reason for this may be that L2 listeners have ample experience with segmental deviations that are characteristic for their own accent. On this account, only phonemic deviations that are typical for the listeners’ own accent will cause spurious lexical activation in L2 listening (e.g., English magic pronounced as megic for Dutch listeners). In this talk, I will present evidence from cross-modal priming studies with a variety of L2 listener groups, showing how the processing of phonemic deviations is accent-specific but withstands fine phonetic differences.

Abstract

In this paper, we present empirical data from a corpus study on the linear order of subjects and objects in German main clauses. The aim was to establish the validity of three well-known ordering constraints: given complements tend to occur before new complements, definite before indefinite, and pronoun before full noun phrase complements. Frequencies of occurrences were derived for subject-first and object-first sentences from the German Negra corpus. While all three constraints held on subject-first sentences, results for object-first sentences varied. Our findings suggest an influence of grammatical functions on the ordering of verb complements.

Abstract

Lexica play an important role in every linguistic discipline. We are confronted with many types of lexica. Depending on the type of lexicon and the language we are currently faced with a large variety of structures from very simple tables to complex graphs, as was indicated by a recent overview of structures found in dictionaries from field linguistics and language engineering. It is important to assess these differences and aim at the integration of lexical resources in order to improve lexicon creation, exchange and reuse. This paper describes the first step towards the integration of existing structures and standards into a flexible abstract model.

Abstract

The increasing quantity and complexity of language resources leads to new management problems for those that collect and those that need to preserve them. At the same time the desire to make these resources available on the Internet demands an efficient way characterizing their properties to allow discovery and re-use. The use of metadata is seen as a solution for both these problems. However, the question is what specific requirements there are for the specific domain and if these are met by existing frameworks. Any possible solution should be evaluated with respect to its merit for solving the domain specific problems but also with respect to its future embedding in “global” metadata frameworks as part of the Semantic Web activities.

Abstract

It is unknown whether modality affects the efficiency with which humans learn novel word forms and their meanings, with previous studies reporting both written and auditory advantages. The current study implements controls whose absence in previous work likely offers explanation for such contradictory findings. In two novel word learning experiments, participants were trained and tested on pseudoword - novel object pairs, with controls on: modality of test, modality of meaning, duration of exposure and transparency of word form. In both experiments word forms were presented in either their written or spoken form, each paired with a pictorial meaning (novel object). Following a 20-minute filler task, participants were tested on their ability to identify the picture-word form pairs on which they were trained. A between subjects design generated four participant groups per experiment 1) written training, written test; 2) written training, spoken test; 3) spoken training, written test; 4) spoken training, spoken test. In Experiment 1 the written stimulus was presented for a time period equal to the duration of the spoken form. Results showed that when the duration of exposure was equal, participants displayed a written training benefit. Given words can be read faster than the time taken for the spoken form to unfold, in Experiment 2 the written form was presented for 300 ms, sufficient time to read the word yet 65% shorter than the duration of the spoken form. No modality effect was observed under these conditions, when exposure to the word form was equivalent. These results demonstrate, at least for proficient readers, that when exposure to the word form is controlled across modalities the efficiency with which word form-meaning associations are learnt does not differ. Our results therefore suggest that, although we typically begin as aural-only word learners, we ultimately converge on developing learning mechanisms that learn equally efficiently from both written and spoken materials.