Publications

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

Annotations of media recordings are the grounds for linguistic research. Since creating those annotations is a very laborious task, reaching 100 times longer than the length of the annotated media, innovative audio and video processing algorithms are needed, in order to improve the efficiency and quality of annotation process. The AVATecH project, started by the Max-Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS, aims at significantly speeding up the process of creating annotations of audio-visual data for humanities research. In order for this to be achieved a range of state-of-the-art audio and video pattern recognition algorithms have been developed and integrated into widely used ELAN annotation tool. To address the problem of heterogeneous annotation tasks and recordings we provide modular components extended by adaptation and feedback mechanisms to achieve competitive annotation quality within significantly less annotation time.

Abstract

Evolution and changes of all modern languages is a well-known fact. However, recently it is reaching dynamics never seen before, which results in loss of the vast amount of information encoded in every language. In order to preserve such heritage, properly annotated recordings of world languages are necessary. Since creating those annotations is a very laborious task, reaching times 100 longer than the length of the annotated media, innovative video processing algorithms are needed, in order to improve the efficiency and quality of annotation process.

Abstract

Processing medical data has always been an interesting field that has shown the need for effective image segmentation methods. Modern medical image segmentation solutions are focused on 3D image volumes, which originate at advanced acquisition devices. Operating on such data in a 3D envi- ronment is essential in order to take the full advantage of the available information. In this paper we present an extended version of our 3D image segmentation and reconstruction model that belongs to the family of Deformable Models and is capable of processing large image volumes in competitive times and in fully 3D environment, offering a big level of automation of the process and a high precision of results. It is also capable of handling topology changes and offers a very good scalability on multi-processing unit architectures. We present a description of the model and show its capabilities in the field of medical image processing.

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

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

How are the senses structured by the languages we speak, the cultures we inhabit? To what extent is the encoding of perceptual experiences in languages a matter of how the mind/brain is ―wired-up‖ and to what extent is it a question of local cultural preoccupation? The ―Language of Perception‖ project tests the hypothesis that some perceptual domains may be more ―ineffable‖ – i.e. difficult or impossible to put into words – than others. While cognitive scientists have assumed that proximate senses (olfaction, taste, touch) are more ineffable than distal senses (vision, hearing), anthropologists have illustrated the exquisite variation and elaboration the senses achieve in different cultural milieus. The project is designed to test whether the proximate senses are universally ineffable – suggesting an architectural constraint on cognition – or whether they are just accidentally so in Indo-European languages, so expanding the role of cultural interests and preoccupations. To address this question, a standardized set of stimuli of color patches, geometric shapes, simple sounds, tactile textures, smells and tastes have been used to elicit descriptions from speakers of more than twenty languages—including three sign languages. The languages are typologically, genetically and geographically diverse, representing a wide-range of cultures. The communities sampled vary in subsistence modes (hunter-gatherer to industrial), ecological zones (rainforest jungle to desert), dwelling types (rural and urban), and various other parameters. We examine how codable the different sensory modalities are by comparing how consistent speakers are in how they describe the materials in each modality. Our current analyses suggest that taste may, in fact, be the most codable sensorial domain across languages. Moreover, we have identified exquisite elaboration in the olfactory domains in some cultural settings, contrary to some contemporary predictions within the cognitive sciences. These results suggest that differential codability may be at least partly the result of cultural preoccupation. This shows that the senses are not just physiological phenomena but are constructed through linguistic, cultural and social practices.

Abstract

To study concepts, cognitive scientists must first identify some. The prevailing assumption is that they are revealed by words such as triangle, table, and robin. But languages vary dramatically in how they carve up the world by name. Either ordinary concepts must be heavily language-dependent or names cannot be a direct route to concepts. We asked English, Dutch, Spanish, and Japanese speakers to name videos of human locomotion and judge their similarities. We investigated what name inventories and scaling solutions on name similarity and on physical similarity for the groups individually and together suggest about the underlying concepts. Aggregated naming and similarity solutions converged on results distinct from the answers suggested by the word inventories and scaling solutions of any single language. Words such as triangle, table, and robin can help identify the conceptual space of a domain, but they do not directly reveal units of knowledge usefully considered 'concepts'.

Abstract

Visual and auditory channels have different affordances and
this is mirrored in what information is available for linguistic
encoding. The visual channel has high spatial acuity, whereas
the auditory channel has better temporal acuity. These
differences may lead to different conceptualizations of events
and affect multimodal language production. Previous studies of
motion events typically present visual input to elicit speech and
gesture. The present study compared events presented as audio-
only, visual-only, or multimodal (visual+audio) input and
assessed speech and co-speech gesture for path and manner of
motion in Turkish. Speakers with audio-only input mentioned
path more and manner less in verbal descriptions, compared to
speakers who had visual input. There was no difference in the
type or frequency of gestures across conditions, and gestures
were dominated by path-only gestures. This suggests that input
modality influences speakers’ encoding of path and manner of
motion events in speech, but not in co-speech gestures.

Abstract

How listeners understand spoken words despite massive variation in the speech signal is a central issue for linguistic theory. A recent focus on lexical frequency and specificity has proved fruitful in accounting for this phenomenon. Speech perception, though, is a multi-faceted process and likely incorporates a number of mechanisms to map a variable signal to meaning. We examine a well-established language use factor — lexical frequency — and how this factor is integrated with phonetic variability during the perception of accented speech. We show that an integrated perspective highlights a low-level perceptual mechanism that accounts for the perception of accented speech absent native contrasts, while shedding light on the use of interactive language factors in the perception of spoken words.

Abstract

The results of a study on perceptual learning are reported. Dutch subjects made lexical decisions on a list of words and nonwords. Embedded in the list were either [f]- or [s]-final words in which the final fricative had been replaced by an ambiguous sound, midway between [f] and [s]. One group of listeners heard ambiguous [f]- final Dutch words like [kara?] (based on karaf, carafe) and unambiguous [s]-final words (e.g., karkas, carcase). A second group heard the reverse (e.g., ambiguous [karka?] and unambiguous karaf). After this training phase, listeners labelled ambiguous fricatives on an [f]- [s] continuum. The subjects who had heard [?] in [f]- final words categorised these fricatives as [f] reliably more often than those who had heard [?] in [s]-final words. These results suggest that speech recognition is dynamic: the system adjusts to the constraints of each particular listening situation. The lexicon can provide this adjustment process with a training signal.

Abstract

Recurrent neural networks (RNNs) have long been an architecture of interest for computational models of human sentence processing. The recently introduced Transformer architecture outperforms RNNs on many natural language processing tasks but little is known about its ability to model human language processing. We compare Transformer- and RNN-based language models’ ability to account for measures of human reading effort. Our analysis shows Transformers to outperform RNNs in explaining self-paced reading times and neural activity during reading English sentences, challenging the widely held idea that human sentence processing involves recurrent and immediate processing and provides evidence for cue-based retrieval.

Abstract

This study addresses the question whether visually grounded speech recognition (VGS) models learn to capture sentence semantics without access to any prior linguistic knowledge. We produce synthetic and natural spoken versions of a well known semantic textual similarity database and show that our VGS model produces embeddings that correlate well with human semantic similarity judgements. Our results show that a model trained on a small image-caption database outperforms two models trained on much larger databases, indicating that database size is not all that matters. We also investigate the importance of having multiple captions per image and find that this is indeed helpful even if the total number of images is lower, suggesting that paraphrasing is a valuable learning signal. While the general trend in the field is to create ever larger datasets to train models on, our findings indicate other characteristics of the database can just as important.

Abstract

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

Speakers tend to take over the articulatory habits of their interlocutors [e.g., Pardo, JASA (2006)]. This phonetic alignment could be the consequence of either a social mechanism or a direct and automatic link between speech perception and production. The latter assumes that social variables should have little influence on phonetic alignment. To test that participants were engaged in a "cloze task" (i.e., Stimulus: "In fantasy movies, silver bullets are used to kill ..." Response: "werewolves") with either one or four interlocutors. Given findings with the Asch-conformity paradigm in social psychology, multiple consistent speakers should exert a stronger force on the participant to align. To control the speech style of the interlocutors, their questions and answers were pre-recorded in either a formal or a casual speech style. The stimuli's speech style was then manipulated between participants and was consistent throughout the experiment for a given participant. Surprisingly, participants aligned less with the speech style if there were multiple interlocutors. This may reflect a "diffusion of responsibility:" Participants may find it more important to align when they interact with only one person than with a larger group.

Abstract

The central issues in the study of speech recognition by human listeners (HSR) and of automatic speech recognition (ASR) are clearly comparable; nevertheless the research communities that concern themselves with ASR and HSR are largely distinct. This paper compares the research objectives of the two fields, and attempts to draw informative lessons from one to the other.

Abstract

Language emergence is characterized by a high degree of lex-
ical variation. It has been suggested that the speed at which
lexical conventionalization occurs depends partially on social
structure. In large communities, individuals receive input from
many sources, creating a pressure for lexical convergence.
In small, insular communities, individuals can remember id-
iolects and share common ground with interlocuters, allow-
ing these communities to retain a high degree of lexical vari-
ation. We look at lexical variation in Kata Kolok, a sign lan-
guage which emerged six generations ago in a Balinese vil-
lage, where women tend to have more tightly-knit social net-
works than men. We test if there are differing degrees of lexical
uniformity between women and men by reanalyzing a picture
description task in Kata Kolok. We find that women’s produc-
tions exhibit less lexical uniformity than men’s. One possible
explanation of this finding is that women’s more tightly-knit
social networks allow for remembering idiolects, alleviating
the pressure for lexical convergence, but social network data
from the Kata Kolok community is needed to support this ex-
planation.

Abstract

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

This paper describes the Glottolog/Langdoc project, an at- tempt to provide near-total bibliographical coverage of descriptive re- sources to the world's languages. Every reference is treated as a resource, as is every \languoid"[1]. References are linked to the languoids which they describe, and languoids are linked to the references described by them. Family relations between languoids are modeled in SKOS, as are relations across dierent classications of the same languages. This setup allows the representation of languoids as collections of references, render- ing the question of the denition of entities like `Scots', `West-Germanic' or `Indo-European' more empirical.

Abstract

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

Abstract

Current models of spoken-word recognition assume automatic activation of multiple candidate words fully or partially compatible with the speech input. We propose that listeners make use of this concurrent activation in word play such as punning. Distortion in punning should ideally involve no more than a minimal contrastive deviation between two words, namely a phoneme. Moreover, we propose that this metric of similarity does not presuppose phonemic awareness on the part of the punster. We support these claims with an analysis of modern and traditional puns in Japanese (in which phonemic awareness in language users is not encouraged by alphabetic orthography). For both data sets, the results support the predictions. Punning draws on basic processes of spokenword recognition, common across languages.

Abstract

Two groups of participants were trained to perceive an ambiguous sound [s/f] as either /s/ or /f/ based on lexical bias: One group heard the ambiguous fricative in /s/-final words, the other in /f/-final words. This kind of exposure leads to a recalibration of the /s/-/f/ contrast [e.g., 4]. In order to investigate when and how this recalibration emerges, test trials were interspersed among training and filler trials. The learning effect needed at least 10 clear training items to arise. Its emergence seemed to occur in a rather step-wise fashion. Learning did not improve much after it first appeared. It is likely, however, that the early test trials attracted participants' attention and therefore may have interfered with the learning process.

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

An exposure-test paradigm was used to examine whether Dutch listeners can adapt their perception to non-canonical marking of lexical stress in Hungarian-accented Dutch. During exposure, one group of listeners heard only words with correct initial stress, while another group also heard examples of unstressed initial syllables that were marked by high pitch, a possible stress cue in Dutch. Subsequently, listeners’ eye movements to target-competitor pairs with segmental overlap but different stress patterns were tracked while hearing Hungarian-accented Dutch. Listeners who had heard non-canonically produced words previously distinguished target-competitor pairs faster than listeners who had only been exposed to canonical forms before. This suggests that listeners can adapt quickly to speaker-specific realizations of non-canonical lexical stress.

Abstract

Listeners can flexibly retune category boundaries of their native language to adapt to non-canonically produced phonemes. This only occurs, however, if the pronunciation peculiarities can be attributed to stable and not transient speaker-specific characteristics. Listening to someone speaking a second language, listeners could attribute non-canonical pronunciations either to the speaker or to the fact that she is modifying her categories in the second language. We investigated whether, following exposure to Dutch-accented English, Dutch listeners show effects of category retuning during test where they hear the same speaker speaking her native language, Dutch. Exposure was a lexical-decision task where either word-final [f] or [s] was replaced by an ambiguous sound. At test listeners categorized minimal word pairs ending in sounds along an [f]-[s] continuum. Following exposure to English words, Dutch listeners showed boundary shifts of a similar magnitude as following exposure to the same phoneme variants in their native language. This suggests that production patterns in a second language are deemed a stable characteristic. A second experiment suggests that category retuning also occurs when listeners are exposed to and tested with a native speaker of their second language. Listeners thus retune phoneme boundaries across languages.

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

The current study reports the enhancing effect of a high variability training procedure in the learning of a Japanese geminate-singleton fricative contrast. Dutch natives took part in a five-day training procedure in which they identified geminate and singleton variants of the Japanese fricative /s/. They heard either many repetitions of a limited set of words recorded by a single speaker (simple training) or fewer repetitions of a more variable set of words recorded by multiple speakers (variable training). Pre-post identification evaluations and a transfer test indicated clear benefits of the variable training.

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

The use of word order and intonation to mark focus in child speech has received some attention. However, past work usually examined each device separately or only compared the realizations of focused vs. non-focused constituents. This paper investigates the interaction between word order and intonation in the marking of different focus types in 4- to 5-year old German-speaking children and an adult control group. An answer-reconstruction task was used to elicit syntactic (word order) and intonational focus marking of subject and objects (locus of focus) in three focus types (broad, narrow, and contrastive focus). The results indicate that both children and adults used intonation to distinguish broad from contrastive focus but they differed in the marking of narrow focus. Further, both groups preferred intonation to word order as device for focus marking. But children showed an early sensitivity for the impact of focus type and focus location on word order variation and on phonetic means to mark focus.

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

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

So far most attempts to automate Directory Assistance services focused on private listings, because it is not known precisely how callers will refer to a business listings. The research described in this paper, carried out in the SMADA project, tries to fill this gap. The aim of the research is to model the expressions people use when referring to a business listing by means of rules, in order to automatically create a vocabulary, which can be part of an automated DA service. In this paper a rule-base procedure is proposed, which derives rules from the expressions people use. These rules are then used to automatically create expressions from directory listings. Two categories of businesses, viz. hospitals and the hotel and catering industry, are used to explain this procedure. Results for these two categories are used to discuss the problem of the over- and undergeneration of expressions.

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

Previous research on lexically-guided perceptual learning has focussed on contrasts that differ primarily in local cues, such as plosive and fricative contrasts. The present research had two aims: to investigate whether perceptual learning occurs for a contrast with non-local cues, the /l/-/r/ contrast, and to establish whether STRAIGHT can be used to create ambiguous sounds on an /l/-/r/ continuum. Listening experiments showed lexically-guided learning about the /l/-/r/ contrast. Listeners can thus tune in to unusual speech sounds characterised by non-local cues. Moreover, STRAIGHT can be used to create stimuli for perceptual learning experiments, opening up new research possibilities. Index Terms: perceptual learning, morphing, liquids, human word recognition, STRAIGHT.

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

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

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

Abstract

ELAN is a multimedia annotation tool that has been developed for roughly ten years now and is still being extended and improved in, on average, two or three major updates per year. This paper describes the current state of the application, the main areas of attention of the past few years and the plans for the near future. The emphasis will be on various interoperability issues: interoperability with other tools through file conversions, process based interoperability with other tools by means of commands send to or received from other applications, interoperability on the level of the data model and semantic interoperability.

Abstract

Computational models of reading have differed in terms of whether they propose a single route forming the mapping between orthography and phonology or whether there is a lexical/sublexical route distinction. A critical test of the architecture of the reading system is how it deals with multi-letter graphemes. Rastle and Coltheart (1998) found that the presence of digraphs in nonwords but not in words led to an increase in naming times, suggesting that nonwords were processed via a distinct sequential route to words. In contrast Pagliuca, Monaghan, and McIntosh (2008) implemented a single route model of reading and showed that under conditions of visual noise the presence of digraphs in words did have an effect on naming accuracy. In this study, we investigated whether such digraph effects could be found in both words and nonwords under conditions of visual noise. If so it would suggest that effects on words and nonwords are comparable. A single route connectionist model of reading showed greater accuracy for both words and nonwords containing digraphs. Experimental results showed participants were more accurate in recognising words if they contained digraphs. However contrary to model predictions they were less accurate in recognising nonwords containing digraphs compared to controls. We discuss the challenges faced by both theoretical perspectives in interpreting these findings and in light of a psycholinguistic grain size theory of reading.

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

Mirror mimicry has well-known consequences for the person being mimicked: it increases how positively they feel about the mimicker (the Chameleon Effect). Here we show that anatomical mimicry has the opposite social consequences: a Reverse-Chameleon Effect. To equate mirror and anatomical mimicry, we asked participants to have a face-to-face conversation with a digital human (VIRTUO), in a fully-immersive virtual environment. Participants’ spontaneous head movements were tracked, and VIRTUO mimicked them at a 2-second delay, either mirror-wise, anatomically, or not at all (instead enacting another participant’s movements). Participants who were mimicked mirror-wise rated their social interaction with VIRTUO to be significantly more positive than those who were mimicked anatomically. Participants who were not mimicked gave intermediate ratings. Beyond its practical implications, the Reverse-Chameleon Effect constrains theoretical accounts of how mimicry affects social perception

Abstract

The Language Archive manages one of the largest and most varied sets of natural language data. This data consists of video and audio enriched with annotations. It is available for more than 250 languages, many of which are endangered. Researchers have a need to access this data conveniently and efficiently. We provide several browse and search methods to cover this need, which have been developed and expanded over the years. Metadata and content-oriented search methods can be connected for a more focused search. This article aims to provide a complete overview of the available search mechanisms, with a focus on annotation content search, including a benchmark.

Abstract

Do listeners use lexical stress at an early stage in word learning? Artificial-lexicon studies have shown that listeners can learn new spoken words easily. These studies used non-words differing in consonants and/or vowels, but not differing only in stress. If listeners use stress information in word learning, they should be able to learn new words that differ only in stress (e.g., BInulo-biNUlo). We investigated this issue here. When learning new words, Italian listeners relied on segmental information; they did not take stress information into account. Newly-acquired words differing in stress alone are not automatically represented as different words.

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

This paper presents a method to quantify the spectral characteristics of reduction in speech. Hämäläinen et al. (2009) proposes a measure of spectral reduction which is able to predict a substantial amount of the variation in duration that linguistically motivated variables do not account for. In this paper, we continue studying acoustic reduction in speech by developing a new acoustic measure of reduction, based on local manifold structure in speech. We show that this measure yields significantly improved statistical models for predicting variation in duration.

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

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

Coordinating with others is hard; and yet we accomplish this every day when we take turns in a conversation. How do we do this? The present study introduces a new method of measuring turn-boundary projection that enables researchers to achieve more valid, flexible, and temporally informative data on online turn projection: tracking an observer’s gaze from the current speaker to the next speaker. In this preliminary investigation, participants consistently looked at the current speaker during their turn. Additionally, they looked to the next speaker before her turn began, and sometimes even before the current speaker finished speaking. This suggests that observer gaze is closely aligned with perceptual processes of turn-boundary projection, and thus may equip the field with the tools to explore how we manage to take turns.

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

In the AVATecH project the Max-Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS aim to significantly speed up the process of creating annotations of audio-visual data for humanities research. For this we integrate state-of-theart audio and video pattern recognition algorithms into the widely used ELAN annotation tool. To address the problem of heterogeneous annotation tasks and recordings we provide modular components extended by adaptation and feedback mechanisms to achieve competitive annotation quality within significantly less annotation time. Currently we are designing a large-scale end-user evaluation of the project.

Abstract

Dialects of the same language can differ in the casual speech processes they allow; e.g., British English allows the insertion of [r] at word boundaries in sequences such as saw ice, while American English does not. In two speeded word recognition experiments, American listeners heard such British English sequences; in contrast to non-native listeners, they accurately perceived intended vowel-initial words even with intrusive [r]. Thus despite input mismatches, cross-dialectal word recognition benefits from the full power of native-language processing.

Abstract

prosodic marking of Verum focus (VF) in Italian, which is said to be realized with a pitch accent on the finite verb (e.g. A: Paul has not eaten the banana - B: (No), Paul HAS eaten the banana!). We tried to discover whether and how Italian speakers prosodically mark VF when producing full-fledged sentences using a semi-spontaneous production experiment on 27 speakers. Speech rate and f0 contours were extracted using automatic data processing tools and were subsequently analysed using Functional Data Analysis (FDA), which allowed for automatic visualization of patterns in the contour shapes. Our results show that the postfocal region of VF sentences exhibit faster speech rate and lower f0 compared to non-VF cases. However, an expected consistent difference of f0 effect on the focal region of the VF sentence was not found in this analysis.

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 research reports the results of eliciting pronouns in two syntactic environments: Object pronouns and quantitative er (Q-er). Thus another type of language is added to the literature on subject and object clitic acquisition in the Romance languages (Jakubowicz et al., 1998; Hamann et al., 1996). Quantitative er is a unique pronoun in the Germanic languages; it has the same distribution as partitive clitics in Romance. Q-er is an N'-anaphor and occurs obligatorily with headless noun phrases with a numeral or weak quantifier. Q-er is licensed only when the context offers an antecedent; it binds an empty position in the NP. Data from typically-developing children aged 5;0-6;0 show that object and Q-er pronouns are not acquired equally; it is proposed that this is due to their different syntax. The use of Q-er involves more sophisticated syntactic knowledge: Q-er occurs at the left edge of the VP and binds an empty position in the NP, whereas object pronouns are simply stand-ins for full NPs and occur in the same position. These Dutch data reveal that pronouns are not used as exclusively as object clitics are in the Romance languages (Varlakosta, in prep.).

Abstract

This paper investigates the effects of novel words on a cognitively plausible computational model of word learning. The model is first familiarized with a set of words, achieving high recognition scores and subsequently offered novel words for training. We show that the model is able to recognize the novel words as different from the previously seen words, based on a measure of novelty that we introduce. We then propose a procedure analogous to novelty preference in infants. Results from simulations of word learning show that adding this procedure to our model speeds up training and helps the model attain higher recognition rates.

Abstract

In this paper an overview of the knowledge components needed for extensive documentation of small languages is given. The Language Archive is striving to offer all these tools to the linguistic community. The major tools in relation to the knowledge components are described. Followed by a discussion on what is currently lacking and possible strategies to move forward.

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

Articulatory data are used to address the question of whether Dutch schwa insertion is a phonological or a phonetic process. By investigating tongue tip raising and dorsal lowering, we show that /l/ when it appears before inserted schwa is a light /l/, just as /l/ before an underlying schwa is, and unlike the dark /l/ before a consonant in non-insertion productions of the same words. The fact that inserted schwa can condition the light/dark /l/ alternation shows that schwa insertion involves the phonological insertion of a segment rather than phonetic adjustments to articulations.

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

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

Understanding speech usually seems easy, but it can become noticeably harder when the speaker has a foreign accent. This is because foreign accents add considerable variation to speech. Research on foreign-accented speech shows that participants are able to adapt quickly to this type of variation. Less is known, however, about longer-term maintenance of adaptation. The current study focused on long-term adaptation by exposing native listeners to foreign-accented speech on Day 1, and testing them on comprehension of the accent one day later. Comprehension was thus not tested immediately, but only after a 24 hour period. On Day 1, native Dutch listeners listened to the speech of a Hebrew learner of Dutch while performing a phoneme monitoring task that did not depend on the talker’s accent. In particular, shortening of the long vowel /i/ into /ɪ/ (e.g., lief [li:f], ‘sweet’, pronounced as [lɪf]) was examined. These mispronunciations did not create lexical ambiguities in Dutch. On Day 2, listeners participated in a cross-modal priming task to test their comprehension of the accent. The results will be contrasted with results from an experiment without delayed testing and related to accounts of how listeners maintain adaptation to foreign-accented speech.