Publications

Abstract

Thesaurus alignment plays an important role in realising efficient access to heterogeneous Cultural Heritage data. Current ontology alignment techniques, however, provide only limited value for such access as they consider little if any requirements from realistic use cases or application scenarios. In this paper, we focus on two real-world scenarios in a library context: thesaurus merging and book re-indexing. We identify their particular requirements and describe our approach of deploying and evaluating thesaurus alignment techniques in this context. We have applied our approach for the Ontology Alignment Evaluation Initiative, and report on the performance evaluation of participants’ tools wrt. the application scenario at hand. It shows that evaluations of tools requires significant effort, but when done carefully, brings many benefits.

Abstract

A common assumption in the cognitive sciences is that artificial and natural language learning rely on shared mechanisms. However, attempts to bridge the two have yielded ambiguous results. We suggest that an empirical disconnect between the computations employed during learning and the methods employed at test may explain these mixed results. Further, we propose statistically-based chunking as a potential computational link between artificial and natural language learning. We compare the acquisition of non-adjacent dependencies to that of natural language structure using two types of tasks: reflection-based 2AFC measures, and processing-based recall measures, the latter being more computationally analogous to the processes used during language acquisition. Our results demonstrate that task-type significantly influences the correlations observed between artificial and natural language acquisition, with reflection-based and processing-based measures correlating within – but not across – task-type. These findings have fundamental implications for artificial-to-natural language comparisons, both methodologically and theoretically.

Abstract

n this study we investigated the durational correlates of lexical stress and pitch accent at normal and fast speech rate in Dutch. Previous literature on English shows that durations of lexically unstressed vowels are reduced more than stressed vowels when speakers increase their speech rate. We found that the same holds for Dutch, irrespective of whether the unstressed vowel is schwa or a "full" vowel. In the same line, we expected that vowels in words without a pitch accent would be shortened relatively more than vowels in words with a pitch accent. This was not the case: if anything, the accented vowels were shortened relatively more than the unaccented vowels. We conclude that duration is an important cue for lexical stress, but not for pitch accent.

Abstract

Studies on fast speech have shown that word-level timing of fast speech differs from that of normal rate speech in that unstressed syllables are shortened more than stressed syllables as speech rate increases. An earlier experiment showed that the intelligibility of time-compressed speech could not be improved by making its temporal organisation closer to natural fast speech. To test the hypothesis that segmental intelligibility is more important than prosodic timing in listening to timecompressed speech, the intelligibility of bisyllabic words was tested in three time-compression conditions: either stressed and unstressed syllable were compressed to the same degree, or the stressed syllable was compressed more than the unstressed syllable, or the reverse. As was found before, imitating wordlevel timing of fast speech did not improve intelligibility over linear compression. However, the results did not confirm the hypothesis either: there was no difference in intelligibility between the three compression conditions. We conclude that segmental intelligibility plays an important role, but further research is necessary to decide between the contributions of prosody and segmental intelligibility to the word-level intelligibility of time-compressed speech.

Abstract

Adult-to-child interactions are often characterized by prosodically-exaggerated speech accompanied by visually captivating co-speech gestures. In a series of adult studies, we have shown that these gestures are linked in a sophisticated manner to the prosodic structure of adults' utterances. In the current study, we use the Preferential Looking Paradigm to demonstrate that two-year-olds can use the alignment of these gestures to speech to deduce the meaning of words.

Abstract

Mutations of the epidermal growth factor receptor (EGFR) gene are found at a relatively high frequency in glioma, with the most common being the de2-7 EGFR (or EGFRvIII). This mutation arises from an in-frame deletion of exons 2-7, which removes 267 amino acids from the extracellular domain of the receptor. Despite being unable to bind ligand, the de2-7 EGFR is constitutively active at a low level. Transfection of human glioma cells with the de2-7 EGFR has little effect in vitro, but when grown as tumor xenografts this mutated receptor imparts a dramatic growth advantage. We mapped the phosphorylation pattern of de2-7 EGFR, both in vivo and in vitro, using a panel of antibodies specific for different phosphorylated tyrosine residues. Phosphorylation of de2-7 EGFR was detected constitutively at all tyrosine sites surveyed in vitro and in vivo, including tyrosine 845, a known target in the wild-type EGFR for src kinase. There was a substantial upregulation of phosphorylation at every yrosine residue of the de2-7 EGFR when cells were grown in vivo compared to the receptor isolated from cells cultured in vitro. Upregulation of phosphorylation at tyrosine 845 could be stimulated in vitro by the addition of specific components of the ECM via an integrindependent mechanism. These observations may partially explain why the growth enhancement mediated by de2-7 EGFR is largely restricted to the in vivo environment

Abstract

Second language (L2) research often involves analyses of acoustic measures of fluency. The studies investigating fluency, however, have been difficult to compare because the measures of fluency that were used differed widely. One of the differences between studies concerns the lower cut-off point for silent pauses, which has been set anywhere between 100 ms and 1000 ms. The goal of this paper is to find an optimal cut-off point. We calculate acoustic measures of fluency using different pause thresholds and then relate these measures to a measure of L2 proficiency and to ratings on fluency.

Abstract

It has been suggested that some individuals may benefit more from social robots than do others. Using second
language (L2) as an example, the present study examined how individual differences in attitudes toward robots and personality
traits may be related to learning outcomes. Preliminary results with 24 Turkish-speaking adults suggest that negative attitudes
toward robots, more specifically thoughts and anxiety about the negative social impact that robots may have on the society,
predicted how well adults learned L2 words from a social robot. The possible implications of the findings as well as future directions are also discussed

Abstract

The ”download first, then process paradigm” is still the predominant working method amongst the research community. The web-based paradigm, however, offers many advantages from a tool development and data management perspective as they allow a quick adaptation to changing research environments. Moreover, new ways of combining tools and data are increasingly becoming available and will eventually enable a true web-based workflow approach, thus challenging the ”download first, then process” paradigm. The necessary infrastructure for managing, exploring and enriching language resources via the Web will need to be delivered by projects like CLARIN and DARIAH

Abstract

In this paper, we describe a unifying approach to tackle data heterogeneity issues for lexica and related resources. We present LEXUS, our software that implements the Lexical Markup Framework (LMF) to uniformly describe and manage lexica of different structures. LEXUS also makes use of a central Data Category Registry (DCR) to address terminological issues with regard to linguistic concepts as well as the handling of working and object languages. Finally, we report on ViCoS, a LEXUS extension, providing support for the definition of arbitrary semantic relations between lexical entries or parts thereof.

Abstract

To achieve true interoperability for valuable linguistic resources different levels of variation need to be addressed. ISO Technical Committee 37, Terminology and other language and content resources, is developing a Data Category Registry. This registry will provide a reusable set of data categories. A new implementation, dubbed ISOcat, of the registry is currently under construction. This paper shortly describes the new data model for data categories that will be introduced in this implementation. It goes on with a sketch of the standardization process. Completed data categories can be reused by the community. This is done by either making a selection of data categories using the ISOcat web interface, or by other tools which interact with the ISOcat system using one of its various Application Programming Interfaces. Linguistic resources that use data categories from the registry should include persistent references, e.g. in the metadata or schemata of the resource, which point back to their origin. These data category references can then be used to determine if two or more resources share common semantics, thus providing a level of interoperability close to the source data and a promising layer for semantic alignment on higher levels

Abstract

Why do languages have the categories they do? It has been argued that spatial terms in the world’s languages reflect categories that support highly informative communication, and that this accounts for the spatial categories found across languages. However, this proposal has been tested against only nine languages, and in a limited fashion. Here, we consider two new languages: Maijɨki, an under-documented language of Peruvian Amazonia, and English. We analyze spatial data from these two new languages and the original nine, using thorough and theoretically targeted computational tests. The results support the hypothesis that spatial terms across dissimilar languages enable near-optimally informative communication, over an influential competing hypothesis

Abstract

Words can be distinguished by segmental differences or by suprasegmental differences or both. Studies from English suggest that suprasegmentals play little role in human spoken-word recognition; English stress, however, is nearly always unambiguously coded in segmental structure (vowel quality); this relationship is less close in Dutch. The present study directly compared the effects of segmental and suprasegmental mispronunciation on word recognition in Dutch. There was a strong effect of suprasegmental mispronunciation, suggesting that Dutch listeners do exploit suprasegmental information in word recognition. Previous findings indicating the effects of mis-stressing for Dutch differ with stress position were replicated only when segmental change was involved, suggesting that this is an effect of segmental rather than suprasegmental processing.

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

A recurrently connected attractor neural network with a Hebbian learning rule is currently our best ANN analogy for a piece cortex. Functionally biological memory operates on a spectrum of time scales with regard to induction and retention, and it is modulated in complex ways by sub-cortical neuromodulatory systems. Moreover, biological memory networks are commonly believed to be highly distributed and engage many co-operating cortical areas. Here we focus on the temporal aspects of induction and retention of memory in a connectionist type attractor memory model of a piece of cortex. A continuous time, forgetful Bayesian-Hebbian learning rule is described and compared to the characteristics of LTP and LTD seen experimentally. More generally, an attractor network implementing this learning rule can operate as a long-term, intermediate-term, or short-term memory. Modulation of the print-now signal of the learning rule replicates some experimental memory phenomena, like e.g. the von Restorff effect.

Abstract

Citations play a crucial role in the scientific discourse, in information retrieval, and in bibliometrics. Many initiatives are currently promoting the idea of having free and open citation data. Creation of citation data, however, is not part of the cataloging workflow in libraries nowadays.
In this paper, we present our project Linked Open Citation Database, in which we design distributed processes and a system infrastructure based on linked data technology. The goal is to show that efficiently cataloging citations in libraries using a semi-automatic approach is possible. We specifically describe the current state of the workflow and its implementation. We show that we could significantly improve the automatic reference extraction that is crucial for the subsequent data curation. We further give insights on the curation and linking process and provide evaluation results that not only direct the further development of the project, but also allow us to discuss its overall feasibility.

Abstract

It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the wine's color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged.

Abstract

Research in body language with use of gesture recognition and speech analysis has gained much attention in the recent times, influencing disciplines related to image and speech processing.

This study aims to design the Media Query Language (MQL) (Lenkiewicz, et al. 2012) combined with the Linguistic Media Query Interface (LMQI) for Elan (Wittenburg, et al. 2006). The system integrated with the new achievements in audio-video recognition will allow querying media files with predefined gesture phases (or motion primitives) and speech characteristics as well as combinations of both. For the purpose of this work the predefined motions and speech characteristics are called patterns for atomic elements and actions for a sequence of patterns. The main assumption is that a user-customized library of patterns and actions and automated media annotation with LMQI will reduce annotation time, hence decreasing costs of creation of annotated corpora. Increase of the number of annotated data should influence the speed and number of possible research in disciplines in which human multimodal interaction is a subject of interest and where annotated corpora are required.

Abstract

Digital processing of medical images has helped physicians and patients during past years by allowing examination and diagnosis on a very precise level. Nowadays possibly the biggest deal of support it can offer for modern healthcare is the use of high performance computing architectures to treat the huge amounts of data that can be collected by modern acquisition devices. This paper presents a parallel processing implementation of an image segmentation algorithm that operates on a computer cluster equipped with 10 processing units. Thanks to well-organized distribution of the workload we manage to significantly shorten the execution time of the developed algorithm and reach a performance gain very close to linear.

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

We present the Narrative Brain Dataset, an fMRI dataset that was collected during spoken presentation of short excerpts of three
stories in Dutch. Together with the brain imaging data, the dataset contains the written versions of the stimulation texts. The texts are
accompanied with stochastic (perplexity and entropy) and semantic computational linguistic measures. The richness and unconstrained
nature of the data allows the study of language processing in the brain in a more naturalistic setting than is common for fMRI studies.
We hope that by making NBD available we serve the double purpose of providing useful neural data to researchers interested in natural
language processing in the brain and to further stimulate data sharing in the field of neuroscience of language.

Abstract

Young children demonstrate the ability to make inferences about the preferences of other agents based on their choices. However, there exists no overarching account of what children are doing when they learn about preferences or how they use that knowledge. We use a rational model of preference learning, drawing on ideas from economics and computer science, to explain the behavior of children in several recent experiments. Specifically, we show how a simple econometric model can be extended to capture two- to four-year-olds’ use of statistical information in inferring preferences, and their generalization of these preferences.

Abstract

We examined how communicators can switch between speaker and listener role with such accurate timing. During conversations, the majority of role transitions happens with a gap or overlap of only a few hundred milliseconds. This suggests that listeners can predict when the turn of the current speaker is going to end. Our hypothesis is that listeners know when a turn ends because they know how it ends. Anticipating the last words of a turn can help the next speaker in predicting when the turn will end, and also in anticipating the content of the turn, so that an appropriate response can be prepared in advance. We used the stimuli material of an earlier experiment (De Ruiter, Mitterer & Enfield, 2006), in which subjects were listening to turns from natural conversations and had to press a button exactly when the turn they were listening to ended. In the present experiment, we investigated if the subjects can complete those turns when only an initial fragment of the turn is presented to them. We found that the subjects made better predictions about the last words of those turns that had more accurate responses in the earlier button press experiment.

Abstract

For (semi-)automated subject indexing systems in digital libraries, it is often more practical to use metadata such as the title of a publication instead of the full-text or the abstract. Therefore, it is desirable to have good text mining and text classification algorithms that operate well already on the title of a publication. So far, the classification performance on titles is not competitive with the performance on the full-texts if the same number of training samples is used for training. However, it is much easier to obtain title data in large quantities and to use it for training than full-text data. In this paper, we investigate the question how models obtained from training on increasing amounts of title training data compare to models from training on a constant number of full-texts. We evaluate this question on a large-scale dataset from the medical domain (PubMed) and from economics (EconBiz). In these datasets, the titles and annotations of millions of publications are available, and they outnumber the available full-texts by a factor of 20 and 15, respectively. To exploit these large amounts of data to their full potential, we develop three strong deep learning classifiers and evaluate their performance on the two datasets. The results are promising. On the EconBiz dataset, all three classifiers outperform their full-text counterparts by a large margin. The best title-based classifier outperforms the best full-text method by 9.4%. On the PubMed dataset, the best title-based method almost reaches the performance of the best full-text classifier, with a difference of only 2.9%.

Abstract

The human body is unique: it is both an object of perception and the source of human experience. Its universality makes it a perfect resource for asking questions about how cognition, brain and typology relate to one another. For example, we can ask how speakers of different languages segment and categorize the human body. A dominant view is that body parts are “given” by visual perceptual discontinuities, and that words are merely labels for these visually determined parts (e.g., Andersen, 1978; Brown, 1976; Lakoff, 1987). However, there are problems with this view. First it ignores other perceptual information, such as somatosensory and motoric representations. By looking at the neural representations of sesnsory representations, we can test how much of the categorization of the human body can be done through perception alone. Second, we can look at language typology to see how much universality and variation there is in body-part categories. A comparison of a range of typologically, genetically and areally diverse languages shows that the perceptual view has only limited applicability (Majid, Enfield & van Staden, in press). For example, using a “coloring-in” task, where speakers of seven different languages were given a line drawing of a human body and asked to color in various body parts, Majid & van Staden (in prep) show that languages vary substantially in body part segmentation. For example, Jahai (Mon-Khmer) makes a lexical distinction between upper arm, lower arm, and hand, but Lavukaleve (Papuan Isolate) has just one word to refer to arm, hand, and leg. This shows that body part categorization is not a straightforward mapping of words to visually determined perceptual parts.

Abstract

Many studies in cognitive science address how people categorize objects, but there has been comparatively little research on event categorization. This study investigated the categorization of events involving material destruction, such as “cutting” and “breaking”. Speakers of 28 typologically, genetically, and areally diverse languages described events shown in a set of video-clips. There was considerable cross-linguistic agreement in the dimensions along which the events were distinguished, but there was variation in the number of categories and the placement of their boundaries.

Abstract

Since the cognitive revolution, a widely held assumption has been that—whereas content may vary across cultures—cognitive processes would be universal, especially those on the more basic levels. Even if scholars do not fully subscribe to this assumption, they often conceptualize, or tend to investigate, cognition as if it were universal (Henrich, Heine, & Norenzayan, 2010). The insight that universality must not be presupposed but scrutinized is now gaining ground, and cognitive diversity has become one of the hot (and controversial) topics in the field (Norenzayan & Heine, 2005). We argue that, for scrutinizing the cultural dimension of cognition, taking an anthropological perspective is invaluable, not only for the task itself, but for attenuating the home-field disadvantages that are inescapably linked to cross-cultural research (Medin, Bennis, & Chandler, 2010).

Abstract

Lexical knowledge influences how human listeners make decisions about speech sounds. Positive lexical effects (faster responses to target sounds in words than in nonwords) are robust across several laboratory tasks, while negative effects (slower responses to targets in more word-like nonwords than in less word-like nonwords) have been found in phonetic decision tasks but not phoneme monitoring tasks. The present experiments tested whether negative lexical effects are therefore a task-specific consequence of the forced choice required in phonetic decision. We compared phoneme monitoring and phonetic decision performance using the same Dutch materials in each task. In both experiments there were positive lexical effects, but no negative lexical effects. We observe that in all studies showing negative lexical effects, the materials were made by cross-splicing, which meant that they contained perceptual evidence supporting the lexically-consistent phonemes. Lexical knowledge seems to influence phonemic decision-making only when there is evidence for the lexically-consistent phoneme in the speech signal.

Abstract

We briefly describe the Merge model of phonemic decision-making, and, in the light of general arguments about the possible role of feedback in spoken-word recognition, defend Merge's feedforward structure. Merge not only accounts adequately for the data, without invoking feedback connections, but does so in a parsimonious manner.

Abstract

The ultimate goal of our research is to improve an existing speech-based computational model of human speech recognition on the task of simulating the role of fine-grained phonetic information in human speech processing. As part of this work we are investigating articulatory feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. Articulatory feature (AF) modelling of speech has received a considerable amount of attention in automatic speech recognition research. Different approaches have been used to build AF classifiers, most notably multi-layer perceptrons. Recently, deep neural networks have been applied to the task of AF classification. This paper aims to improve AF classification by investigating two different approaches: 1) investigating the usefulness of a deep Convolutional neural network (CNN) for AF classification; 2) integrating the Mel filtering operation into the CNN architecture. The results showed a remarkable improvement in classification accuracy of the CNNs over state-of-the-art AF classification results for Dutch, most notably in the minority classes. Integrating the Mel filtering operation into the CNN architecture did not further improve classification performance.

Abstract

Words are reduced in spontaneous speech. If reductions are constrained by functional (i.e., perception and production) constraints, they should not be arbitrary. This hypothesis was tested by examing the pronunciations of high- to mid-frequency words in a Dutch and a German spontaneous speech corpus. In logistic-regression models the "reduction likelihood" of a phoneme was predicted by fixed-effect predictors such as position within the word, word length, word frequency, and stress, as well as random effects such as phoneme identity and word. The models for Dutch and German show many communalities. This is in line with the assumption that similar functional constraints influence reductions in both languages.

Abstract

Analyzing EEG signals recorded while participants are listening to continuous speech with the purpose of testing linguistic hypotheses is complicated by the fact that the signals simultaneously reflect exogenous acoustic excitation and endogenous linguistic processing. This makes it difficult to trace subtle differences that occur in mid-sentence position. We apply an analysis based on multivariate temporal response functions to uncover subtle mid-sentence effects. This approach is based on a per-stimulus estimate of the response of the neural system to speech input. Analyzing EEG signals predicted on the basis of the response functions might then bring to light conditionspecific differences in the filtered signals. We validate this approach by means of an analysis of EEG signals recorded with isolated word stimuli. Then, we apply the validated method to the analysis of the responses to the same words in the middle of meaningful sentences.

Abstract

Two word-spotting experiments are reported that examine whether the Possible-Word Constraint (PWC) [1] is a language-specific or language-universal strategy for the segmentation of continuous speech. The PWC disfavours parses which leave an impossible residue between the end of a candidate word and a known boundary. The experiments examined cases where the residue was either a CV syllable with a lax vowel, or a CVC syllable with a schwa. Although neither syllable context is a possible word in English, word-spotting in both contexts was easier than with a context consisting of a single consonant. The PWC appears to be language-universal rather than language-specific.

Abstract

Simulations explored the inability of the TRACE model of spoken-word recognition to model the effects on human listening of subcategorical mismatch in word forms. The source of TRACE's failure lay not in interactive connectivity, not in the presence of inter-word competition, and not in the use of phonemic representations, but in the need for continuously optimised interpretation of the input. When an analogue of TRACE was allowed to cycle to asymptote on every slice of input, an acceptable simulation of the subcategorical mismatch data was achieved. Even then, however, the simulation was not as close as that produced by the Merge model, which has inter-word competition, phonemic representations and continuous optimisation (but no interactive connectivity).

Abstract

Natural sign languages and gestures are complex communicative systems that allow the incorporation of features of a referent into their structure. They differ, however, in that signs are more conventionalised because they consist of meaningless phonological parameters. There is some evidence that despite non-signers finding iconic signs more memorable they can have more difficulty at articulating their exact phonological components. In the present study, hearing non-signers took part in a sign repetition task in which they had to imitate as accurately as possible a set of iconic and arbitrary signs. Their renditions showed that iconic signs were articulated significantly less accurately than arbitrary signs. Participants were recalled six months later to take part in a sign generation task. In this task, participants were shown the English translation of the iconic signs they imitated six months prior. For each word, participants were asked to generate a sign (i.e., an iconic gesture). The handshapes produced in the sign repetition and sign generation tasks were compared to detect instances in which both renditions presented the same configuration. There was a significant correlation between articulation accuracy in the sign repetition task and handshape overlap. These results suggest some form of gestural interference in the production of iconic signs by hearing non-signers. We also suggest that in some instances non-signers may deploy their own conventionalised gesture when producing some iconic signs. These findings are interpreted as evidence that non-signers process iconic signs as gestures and that in production, only when sign and gesture have overlapping features will they be capable of producing the phonological components of signs accurately.

Abstract

A database is presented of relative familiarity ratings for 24 sets of Japanese words, each set comprising words overlapping in the initial portions. These ratings are useful for the generation of material sets for research in the recognition of spoken words.

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

Dutch and Spanish differ in how predictable the stress pattern is as a function of the segmental content: it is correlated with syllable weight in Dutch but not in Spanish. In the present study, two experiments were run to compare the abilities of Dutch and Spanish speakers to separately process segmental and stress information. It was predicted that the Spanish speakers would have more difficulty focusing on the segments and ignoring the stress pattern than the Dutch speakers. The task was a speeded classification task on CVCV syllables, with blocks of trials in which the stress pattern could vary versus blocks in which it was fixed. First, we found interference due to stress variability in both languages, suggesting that the processing of segmental information cannot be performed independently of stress. Second, the effect was larger for Spanish than for Dutch, suggesting that that the degree of interference from stress variation may be partially mitigated by the predictability of stress placement in the language.

Abstract

In everyday communication, people not only use speech but
also hand gestures to convey information. One intriguing
question in gesture research has been why gestures take the
specific form they do. Previous research has identified the
speaker-gesturer’s communicative intent as one factor
shaping the form of iconic gestures. Here we investigate
whether communicative intent also shapes the form of
pointing gestures. In an experimental setting, twenty-four
participants produced pointing gestures identifying a referent
for an addressee. The communicative intent of the speakergesturer
was manipulated by varying the informativeness of
the pointing gesture. A second independent variable was the
presence or absence of concurrent speech. As a function of their communicative intent and irrespective of the presence of speech, participants varied the durations of the stroke and the post-stroke hold-phase of their gesture. These findings add to our understanding of how the communicative context influences the form that a gesture takes.

Abstract

Cognitive neuroscience approaches the brain as a cognitive system: a system that functionally is conceptualized in terms of information processing. We outline some aspects of this concept and consider a physical system to be an information processing device when a subclass of its physical states can be viewed as representational/cognitive and transitions between these can be conceptualized as a process operating on these states by implementing operations on the corresponding representational structures. We identify a generic and fundamental problem in cognition: sequentially organized structured processing. Structured sequence processing provides the brain, in an essential sense, with its processing logic. In an approach addressing this problem, we illustrate how to integrate levels of analysis within a framework of adaptive dynamical systems. We note that the dynamical system framework lends itself to a description of asynchronous event-driven devices, which is likely to be important in cognition because the brain appears to be an asynchronous processing system. We use the human language faculty and natural language processing as a concrete example through out.

Abstract

A fundamental ability of speakers is to
quickly retrieve words from long-term memory. According to a prominent theory, concepts activate multiple associated words, which enter into competition for selection. Previous electrophysiological studies have provided evidence for the activation of multiple alternative words, but did not identify brain responses refl ecting competition. We report a magnetoencephalography study examining the timing and neural substrates of lexical activation and competition. The degree of activation of competing words was
manipulated by presenting pictures (e.g., dog) simultaneously with distractor
words. The distractors were semantically related to the picture name (cat), unrelated (pin), or identical (dog). Semantic distractors are stronger competitors to the picture name, because they receive additional activation from the picture, whereas unrelated distractors do not. Picture naming times were longer with semantic than with unrelated and identical distractors. The patterns of phase-locked and non-phase-locked activity were distinct
but temporally overlapping. Phase-locked activity in left middle temporal
gyrus, peaking at 400 ms, was larger on unrelated than semantic and identical trials, suggesting differential effort in processing the alternative words activated by the picture-word stimuli. Non-phase-locked activity in the 4-10 Hz range between 400-650 ms in left superior frontal gyrus was larger on semantic than unrelated and identical trials, suggesting different
degrees of effort in resolving the competition among the alternatives
words, as refl ected in the naming times. These findings characterize distinct
patterns of brain activity associated with lexical activation and competition
respectively, and their temporal relation, supporting the theory that words are selected by competition.

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

Music is a pervasive phenomenon in human culture, and musical
rhythm is virtually present in all musical traditions. Research
on the evolution and cognitive underpinnings of rhythm
can benefit from a number of approaches. We outline key concepts
and definitions, allowing fine-grained analysis of rhythmic
cognition in experimental studies. We advocate comparative
animal research as a useful approach to answer questions
about human music cognition and review experimental evidence
from different species. Finally, we suggest future directions
for research on the cognitive basis of rhythm. Apart from
research in semi-natural setups, possibly allowed by “drum set
for chimpanzees” prototypes presented here for the first time,
mathematical modeling and systematic use of circular statistics
may allow promising advances.

Abstract

Dutch listeners' looks to printed words were tracked while they listened to instructions to click with their mouse on one of them. When presented with targets from word pairs where the first two syllables were segmentally identical but differed in stress location, listeners used stress information to recognize the target before segmental information disambiguated the words. Furthermore, the amount of lexical competition was influenced by the presence or absence of word-initial stress.

Abstract

Segmental as well as suprasegmental information is used by Dutch listeners to recognize words. The time-course of the effect of suprasegmental stress information on spoken-word recognition was investigated in a previous study, in which we tracked Dutch listeners' looks to arrays of four printed words as they listened to spoken sentences. Each target was displayed along with a competitor that did not differ segmentally in its first two syllables but differed in stress placement (e.g., 'CENtimeter' and 'sentiMENT'). The listeners' eye-movements showed that stress information is used to recognize the target before distinct segmental information is available. Here, we examine the role of durational information in this effect. Two experiments showed that initial-syllable duration, as a cue to lexical stress, is not interpreted dependent on the speaking rate of the preceding carrier sentence. This still held when other stress cues like pitch and amplitude were removed. Rather, the speaking rate of the preceding carrier affected the speed of word recognition globally, even though the rate of the target itself was not altered. Stress information modulated lexical competition, but did so independently of the rate of the preceding carrier, even if duration was the only stress cue present.

Abstract

The relationship between individual cognition and cultural phenomena at the society level can be transformed by cultural transmission (Kirby, Dowman, & Griffiths, 2007). Top-down models of this process have typically assumed that individuals only adopt a single linguistic trait. Recent extensions include ‘bilingual’ agents, able to adopt multiple linguistic traits (Burkett & Griffiths, 2010). However, bilingualism is more than variation within an individual: it involves the conditional use of variation with different interlocutors. That is, bilingualism is a property of a population that emerges from use. A bottom-up simulation is presented where learners are sensitive to the identity of other speakers. The simulation reveals that dynamic social structures are a key factor for the evolution of bilingualism in a population, a feature that was abstracted away in the top-down models. Top-down and bottom-up approaches may lead to different answers, but can work together to reveal and explore important features of the cultural transmission process.

Abstract

The recognition of emotions of disgust, anger and fear have been shown to be significantly impaired in Huntington’s disease (eg,Sprengelmeyer et al, 1997, 2006; Gray et al, 1997; Milders et al, 2003,Montagne et al, 2006; Johnson et al, 2007; De Gelder et al, 2008). The relative impairment of these emotions might have implied a recognition impairment specific to negative emotions. Could the asymmetric recognition deficits be due not to the complexity of the emotion but rather reflect the complexity of the task? In the current study, 15 Huntington’s patients and 16 control subjects were presented with negative and positive non-speech emotional vocalisations that were to be identified as anger, fear, sadness, disgust, achievement, pleasure and amusement in a forced-choice paradigm. This experiment more accurately matched the negative emotions with positive emotions in a homogeneous modality. The resulting dually impaired ability of Huntington’s patients to identify negative and positive non-speech emotional vocalisations correctly provides evidence for an overall emotional recognition deficit in the disease. These results indicate that previous findings of a specificity in emotional recognition deficits might instead be due to the limitations of the visual modality. Previous experiments may have found an effect of emotional specificy due to the presence of a single positive emotion, happiness, in the midst of multiple negative emotions. In contrast with the previous literature, the study presented here points to a global deficit in the recognition of emotional sounds.

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

This paper presents the first application of polynomial modeling as a means for validating phonological pitch accent labels to German data. It is compared to traditional phonetic analysis (measuring minima, maxima, alignment). The traditional method fares better in classification, but results are comparable in statistical accent pair testing. Robustness tests show that pitch correction is necessary in both cases. The approaches are discussed in terms of their practicability, applicability to other domains of research and interpretability of their results.

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

We investigated the time course of sentence formulation in Tagalog, a verb-initial language in which the verb obligatorily agrees with one of its arguments. Eye-tracked participants described pictures of transitive events. Fixations to the two characters in the events were compared across sentences differing in agreement marking and post-verbal word order. Fixation patterns show evidence for two temporally dissociated phases in Tagalog sentence production. The first, driven by verb agreement, involves early linking of concepts to syntactic functions; the second, driven by word order, involves incremental lexical encoding of these concepts. These results suggest that even the earliest stages of sentence formulation may be guided by a language's grammatical structure.

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

In the context of the source-filter theory of speech, it is well established that intelligibility is heavily reliant on information carried by the filter, that is, spectral cues (e.g., Faulkner et al., 2001; Shannon et al., 1995). However, the extraction of other types of information in the speech signal, such as emotion and identity, is less well understood. In this study we investigated the extent to which emotion recognition in speech depends on filterdependent cues, using a forced-choice emotion identification task at ten levels of noise-vocoding ranging between one and 32 channels. In addition, participants performed a speech intelligibility task with the same stimuli. Our results indicate that compared to speech intelligibility, emotion recognition relies less on spectral information and more on cues typically signaled by source variations, such as voice pitch, voice quality, and intensity. We suggest that, while the reliance on spectral dynamics is likely a unique aspect of human speech, greater phylogenetic continuity across species may be found in the communication of affect in vocalizations.

Abstract

Research using event-related brain potentials (ERPs) has demonstrated an early differential effect in fronto-central regions when processing emotional, as compared to affectively neutral facial stimuli (e.g., Eimer & Holmes, 2002). In this talk, data demonstrating a similar effect in the auditory domain will be presented. ERPs were recorded in a one-back task where participants had to identify immediate repetitions of emotion category, such as a fearful sound followed by another fearful sound. The stimulus set consisted of non-verbal emotional vocalisations communicating positive and negative sounds, as well as neutral baseline conditions. Similarly to the facial domain, fear sounds as compared to acoustically controlled neutral sounds, elicited a frontally distributed positivity with an onset latency of about 150 ms after stimulus onset. These data suggest the existence of a rapid multi-modal frontocentral mechanism discriminating emotional from non-emotional human 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

Older listeners with high-frequency hearing loss rely more on intensity for categorisation of /s/ than normal-hearing older listeners. This study addresses the question whether this increased reliance comes about immediately when the need
arises, i.e., in the face of a spectrally-degraded signal. A phonetic categorisation task was carried out using intensitymodulated fricatives in a clean and a low-pass filtered condition with two younger and two older listener groups.
When high-frequency information was removed from the speech signal, younger listeners started using intensity as a cue. The older adults on the other hand, when presented with the low-pass filtered speech, did not rely on intensity differences for fricative identification. These results suggest that the reliance on intensity shown by the older hearingimpaired adults may have been acquired only gradually with
longer exposure to a degraded speech signal.

Abstract

Listeners outperform ASR systems in every speech recognition task. However, what is not clear is where this human advantage originates. This paper investigates the role of acoustic feature representations. We test four (MFCCs, PLPs, Mel Filterbanks, Rate Maps) acoustic representations, with and without ‘pitch’ information, using the same backend. The results are compared with listener results at the level of articulatory feature classification. While no acoustic feature representation reached the levels of human performance, both MFCCs and Rate maps achieved good scores, with Rate maps nearing human performance on the classification of voicing. Comparing the results on the most difficult articulatory features to classify showed similarities between the humans and the SVMs: e.g., ‘dental’ was by far the least well identified by both groups. Overall, adding pitch information seemed to hamper classification performance.