Publications

Abstract

The current study reports specific cases in which a positive transfer of perceptual ability from the music domain to the language domain occurs. We tested whether musical training enhances discrimination and identification performance of L2 speech sounds (timing features, nasal consonants and vowels). Native Dutch and Japanese speakers with different musical training experience, matched for their estimated verbal IQ, participated in the experiments. Results indicated that musical training strongly increases one’s ability to perceive timing information in speech signals. We also found a benefit of musical training on discrimination performance for a subset of the tested vowel contrasts.

Abstract

Despite differences in language, culture, and ecology, some human characteristics are similar in people all over the world, while other features vary from one group to the next. These similarities and differences can inform arguments about what aspects of the human mind are part of our shared biological heritage and which are predominantly products of culture and language. I will present data from a cross-cultural project investigating the recognition of non-verbal vocalizations of emotions, such as screams and laughs, across two highly different cultural groups. English participants were compared to individuals from remote, culturally isolated Namibian villages. Vocalizations communicating the so-called “basic emotions” (anger, disgust, fear, joy, sadness, and surprise) were bidirectionally recognised. In contrast, a set of additional positive emotions was only recognised within, but not across, cultural boundaries. These results indicate that a number of primarily negative emotions are associated with vocalizations that can be recognised across cultures, while at least some positive emotions are communicated with culture-specific signals. I will discuss these findings in the context of accounts of emotions at differing levels of analysis, with an emphasis on the often-neglected positive emotions.

Abstract

Many studies suggest that emotional signals can be recognized across cultures and modalities. But to what extent are these signals innate and to what extent are they learned? This study investigated whether auditory learning is necessary for the production of recognizable emotional vocalizations by examining the vocalizations produced by people born deaf. Recordings were made of eight congenitally deaf Dutch individuals, who produced non-verbal vocalizations of a range of negative and positive emotions. Perception was examined in a forced-choice task with hearing Dutch listeners (n = 25). Considerable variability was found across emotions, suggesting that auditory learning is more important for the acquisition of certain types of vocalizations than for others. In particular, achievement and surprise sounds were relatively poorly recognized. In contrast, amusement and disgust vocalizations were well recognized, suggesting that for some emotions, recognizable vocalizations can develop without any auditory learning. The implications of these results for models of emotional communication are discussed, and other routes of social learning available to the deaf individuals are considered.

Abstract

Vocalizations like screams and laughs are used to communicate affective states, but what acoustic cues in these signals require vocal learning and which ones are innate? This study investigated the role of auditory learning in the production of non-verbal emotional vocalizations by examining the vocalizations produced by people born deaf. Recordings were made of congenitally deaf Dutch individuals and matched hearing controls, who produced non-verbal vocalizations of a range of negative and positive emotions. Perception was examined in a forced-choice task with hearing Dutch listeners (n = 25), and judgments were analyzed together with acoustic cues, including envelope, pitch, and spectral measures. Considerable variability was found across emotions and acoustic cues, and the two types of information were related for a sub-set of the emotion categories. These results suggest that auditory learning is less important for the acquisition of certain types of vocalizations than for others (particularly amusement and relief), and they also point to a less central role for auditory learning of some acoustic features in affective non-verbal vocalizations. The implications of these results for models of vocal emotional communication are discussed.

Abstract

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

Abstract

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

Abstract

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

Abstract

This paper presents a study on the acoustic sub-segmental properties of word-final /t/ in conversational standard Dutch and how these properties contribute to whether humans and an ASR system classify the /t/ as acoustically present or absent. In general, humans and the ASR system use the same cues (presence of a constriction, a burst, and alveolar frication), but the ASR system is also less sensitive to fine cues (weak bursts, smoothly starting friction) than human listeners and misled by the presence of glottal vibration. These data inform the further development of models of human and automatic speech processing.

Abstract

Due to its numerous bibliometric entries of scholarly articles and connected information Wikidata can serve as an open and rich
source for deep scientometrical analyses. However, there are currently certain limitations: While 31.5% of all Wikidata entries represent scientific articles, only 8.9% are entries describing a person and the number
of entries researcher is accordingly even lower. Another issue is the frequent absence of established relations between the scholarly article item and the author item although the author is already listed in Wikidata.
To fill this gap and to improve the content of Wikidata in general, we established a workflow for matching authors and scholarly publications by integrating data from the ORCID (Open Researcher and Contributor ID) database. By this approach we were able to extend Wikidata by more than 12k author-publication relations and the method can be
transferred to other enrichments based on ORCID data. This is extension is beneficial for Wikidata users performing bibliometrical analyses or using such metadata for other purposes.

Abstract

Three experiments examined whether infants recognise functors in phrases, and whether their representations of functors are phonetically well specified. Eight- and 13- month-old English infants heard monosyllabic lexical words preceded by real functors (e.g., the, his) versus nonsense functors (e.g., kuh); the latter were minimally modified segmentally (but not prosodically) from real functors. Lexical words were constant across conditions; thus recognition of functors would appear as longer listening time to sequences with real functors. Eightmonth- olds' listening times to sequences with real versus nonsense functors did not significantly differ, suggesting that they did not recognise real functors, or functor representations lacked phonetic specification. However, 13-month-olds listened significantly longer to sequences with real functors. Thus, somewhere between 8 and 13 months of age infants learn familiar functors and represent them with segmental detail. We propose that accumulated frequency of functors in input in general passes a critical threshold during this time.

Abstract

Spontal-N is a corpus of spontaneous, interactional Norwegian. To our knowledge, it is the first corpus of Norwegian in which the majority of speakers have spent significant parts of their lives in Sweden, and in which the recorded speech displays varying degrees of interference from Swedish. The corpus consists of studio quality audio- and video-recordings of four 30-minute free conversations between acquaintances, and a manual orthographic transcription of the entire material. On basis of the orthographic transcriptions, we automatically annotated approximately 50 percent of the material on the phoneme level, by means of a forced alignment between the acoustic signal and pronunciations listed in a dictionary. Approximately seven percent of the automatic transcription was manually corrected. Taking the manual correction as a gold standard, we evaluated several sources of pronunciation variants for the automatic transcription. Spontal-N is intended as a general purpose speech resource that is also suitable for investigating phonetic detail.

Abstract

This paper presents the Kachna corpus of spontaneous speech, in which ten Czech and ten Norwegian speakers were recorded both in their native language and in English. The dialogues are elicited using a picture replication task that requires active cooperation and interaction of speakers by asking them to produce a drawing as close to the original as possible. The corpus is appropriate for the study of interactional features and speech reduction phenomena across native and second languages. The combination of productions in non-native English and in speakers’ native language is advantageous for investigation of L2 issues while providing a L1 behaviour reference from all the speakers. The corpus consists of 20 dialogues comprising 12 hours 53 minutes of recording, and was collected in 2008. Preparation of the transcriptions, including a manual orthographic transcription and an automatically generated phonetic transcription, is currently in progress. The phonetic transcriptions are automatically generated by aligning acoustic models with the speech signal on the basis of the orthographic transcriptions and a dictionary of pronunciation variants compiled for the relevant language. Upon completion the corpus will be made available via the European Language Resources Association (ELRA).

Abstract

Why do people accommodate to each other’s linguistic behavior? Studies of natural interactions (Giles, Taylor & Bourhis, 1973) suggest that speakers accommodate to achieve interactional goals, influencing what their interlocutor thinks or feels about them. But is this the only reason speakers accommodate? In real-world conversations, interactional motivations are ubiquitous, making it difficult to assess the extent to which they drive accommodation. Do speakers still accommodate even when interactional goals cannot be achieved, for instance, when their interlocutor cannot interpret their accommodation behavior? To find out, we asked participants to enter an immersive virtual reality (VR) environment and to converse with a virtual interlocutor. Participants accommodated to the speech rate of their virtual interlocutor even though he could not interpret their linguistic behavior, and thus accommodation could not possibly help them to achieve interactional goals. Results show that accommodation does not require explicit interactional goals, and suggest other social motivations for accommodation.

Abstract

In this article, we propose the use of suffix arrays to efficiently implement n-gram language models with practically unlimited size n. This approach, which is used with synchronous back-off, allows us to distinguish between alternative sequences using large contexts. We also show that we can build this kind of models with additional information for each symbol, such as part-of-speech tags and dependency information. The approach can also be viewed as a collection of virtual k-testable automata. Once built, we can directly access the results of any k-testable automaton generated from the input training data. Synchronous back- off automatically identies the k-testable automaton with the largest feasible k. We have used this approach in several classification tasks.

Abstract

Finding regularities in large data sets requires implementations of systems that are efficient in both time and space requirements. Here, we describe a newly developed system that exploits the internal structure of the enhanced suffixarray to find significant patterns in a large collection of sequences. The system searches exhaustively for all significantly compressing patterns where patterns may consist of symbols and skips or wildcards. We demonstrate a possible application of the system by detecting interesting patterns in a Dutch and an English corpus.

Abstract

In this article, we propose the use of suffix arrays to implement n-gram language models with practically unlimited size n. These unbounded n-grams are called 1-grams. This approach allows us to use large contexts efficiently to distinguish between different alternative sequences while applying synchronous back-off. From a practical point of view, the approach has been applied within the context of spelling confusibles, verb and noun agreement and prenominal adjective ordering. These initial experiments show promising results and we relate the performance to the size of the n-grams used for disambiguation.

Abstract

In face-to-face conversation, recipients might use the bodily movements of the speaker (e.g. gestures) to facilitate language processing. It has been suggested that one way through which this facilitation may happen is prediction. However, for this to be possible, gestures would need to precede speech, and it is unclear whether this is true during natural conversation.
In a corpus of Dutch conversations, we annotated hand gestures that represent semantic information and occurred during questions, and the word(s) which corresponded most closely to the gesturally depicted meaning. Thus, we tested whether representational gestures temporally precede their lexical affiliates. Further, to see whether preceding gestures may indeed facilitate language processing, we asked whether the gesture-speech asynchrony predicts the response time to the question the gesture is part of.
Gestures and their strokes (most meaningful movement component) indeed preceded the corresponding lexical information, thus demonstrating their predictive potential. However, while questions with gestures got faster responses than questions without, there was no evidence that questions with larger gesture-speech asynchronies get faster responses. These results suggest that gestures indeed have the potential to facilitate predictive language processing, but further analyses on larger datasets are needed to test for links between asynchrony and processing advantages.

Abstract

This study investigates phrase-medial vowel devoicing in European French (e.g. /ty po/ [typo] 'you can'). Our spontaneous speech data confirm that French phrase-medial devoicing is a frequent phenomenon affecting high vowels preceded by voiceless consonants. We also found that devoicing is more frequent in temporally reduced and coarticulated vowels. Complete and partial devoicing were conditioned by the same variables (speech rate, consonant type and distance from the end of the AP). Given these results, we propose that phrase-medial vowel devoicing in French arises mainly from the temporal compression of vocalic gestures and the aerodynamic conditions imposed by high vowels.

Abstract

This article describes the preparation, recording and orthographic transcription of a new speech corpus, the Nijmegen Corpus of Casual Spanish (NCCSp). The corpus contains around 30 hours of recordings of 52 Madrid Spanish speakers engaged in conversations with friends. Casual speech was elicited during three different parts, which together provided around ninety minutes of speech from every group of speakers. While Parts 1 and 2 did not require participants to perform any specific task, in Part 3 participants negotiated a common answer to general questions about society. Information about how to obtain a copy of the corpus can be found online at http://mirjamernestus.ruhosting.nl/Ernestus/NCCSp

Abstract

Multilingual speakers are able to switch from
one language to the other (“code-switch”) be-
tween or within sentences. Because the under-
lying cognitive mechanisms are not well un-
derstood, in this study we use computational
cognitive modeling to shed light on the pro-
cess of code-switching. We employed the
Bilingual Dual-path model, a Recurrent Neu-
ral Network of bilingual sentence production
(Tsoukala et al., 2017) and simulated sentence
production in simultaneous Spanish-English
bilinguals. Our first goal was to investigate
whether the model would code-switch with-
out being exposed to code-switched training
input. The model indeed produced code-
switches even without any exposure to such
input and the patterns of code-switches are
in line with earlier linguistic work (Poplack,
1980). The second goal of this study was to
investigate an auxiliary phrase asymmetry that
exists in Spanish-English code-switched pro-
duction. Using this cognitive model, we ex-
amined a possible cause for this asymmetry.
To our knowledge, this is the first computa-
tional cognitive model that aims to simulate
code-switched sentence production.

Abstract

Every language manifests casual speech processes, and hence every second language too. This study examined how listeners deal with second-language casual speech processes, as a function of the processes in their native language. We compared a match case, where a second-language process t/-reduction) is also operative in native speech, with a mismatch case, where a second-language process (/r/-insertion) is absent from native speech. In each case native and non-native listeners judged stimuli in which a given phoneme (in sentence context) varied along a continuum from absent to present. Second-language listeners in general mimicked native performance in the match case, but deviated significantly from native performance in the mismatch case. Together these results make it clear that the mapping from first to second language is as important in the interpretation of casual speech processes as in other dimensions of speech perception. Unfamiliar casual speech processes are difficult to adapt to in a second language. Casual speech processes that are already familiar from native speech, however, are easy to adapt to; indeed, our results even suggest that it is possible for subtle difference in their occurrence patterns across the two languages to be detected,and to be accommodated to in second-language listening.

Abstract

This paper introduces a new CLARIN Knowledge Center which is the K-Centre for Atypical Communication Expertise (ACE for short) which has been established at the Centre for Language and Speech Technology (CLST) at Radboud University. Atypical communication is an umbrella term used here to denote language use by second language learners, people with language disorders or those suffering from language disabilities, but also more broadly by bilinguals and users of sign languages. It involves multiple modalities (text, speech, sign, gesture) and encompasses different developmental stages. ACE closely collaborates with The Language Archive (TLA) at the Max Planck Institute for Psycholinguistics in order to safeguard GDPR-compliant data storage and access. We explain the mission of ACE and show its potential on a number of showcases and a use case.

Abstract

A series of experiments is conducted on naïve native speakers of Dutch and English to study the scope relation between tense and epistemic modality. The results are consistent with the claim that epistemics scope over tense (Stowell 2004, Hacquard 2006, a.o.), and challenge recent research that states that epistemics can, or must, scope under tense (von Fintel and Gillies 2007, Rullmann & Matthewson 2018): Dutch and English participants in a Truth Value Judgment Task judge sentences to be false when the past tense forms of the modals have to and moeten 'have to' are used to make an epistemic claim that held at a time before speech time, and true when they are used to make an epistemic claim that holds at speech time. Moreover, English participants in an Acceptability Judgment Task judge sentences to be infelicitous when the same past tense form of have to is used to make an epistemic claim that held at a time before speech time. Besides these general patterns, the results show variation within and across the two languages, which leads to interesting new questions about the interaction between tense and (epistemic) modality.

Abstract

How can people communicate successfully while keeping resource costs low in the face of ambiguity? We present a principled theoretical analysis comparing two strategies for disambiguation in communication: (i) pragmatic reasoning, where communicators reason about each other, and (ii) other-initiated repair, where communicators signal and resolve trouble interactively. Using agent-based simulations and computational complexity analyses, we compare the efficiency of these strategies in terms of communicative success, computation cost and interaction cost. We show that agents with a simple repair mechanism can increase efficiency, compared to pragmatic agents, by reducing their computational burden at the cost of longer interactions. We also find that efficiency is highly contingent on the mechanism, highlighting the importance of explicit formalisation and computational rigour.

Abstract

Controlled vocabularies of various kinds (e.g., thesauri, classification schemes) play an integral part in making Cultural Heritage collections accessible. The various institutions participating in the Dutch CATCH programme maintain and make use of a rich and diverse set of vocabularies. This makes it hard to provide a uniform point of access to all collections at once. Our SKOS-based vocabulary and alignment repository aims at providing technology for managing the various vocabularies, and for exploiting semantic alignments across any two of them. The repository system exposes web services that effectively support the construction of tools for searching and browsing across vocabularies and collections or for collection curation (indexing), as we demonstrate.

Abstract

Multivariate analysis allows decoding of single trial data in individual subjects. Since different models are obtained for each subject it becomes hard to perform an analysis on the group level. We introduce a new algorithm for Bayesian multi-task learning which imposes a coupling between single-subject models. Using
the CMU fMRI dataset it is shown that the algorithm can be used for concept classification
based on the average activation of regions in the AAL atlas. Concepts which were most easily classified correspond to the categories shelter,manipulation and eating, which is in accordance with the literature. The multi-task learning algorithm is shown to find regions of interest that are common to all subjects which
therefore facilitates interpretation of the obtained
models.

Abstract

This paper reports two experiments with vowels and consonants as phoneme detection targets in real words. In the first experiment, two relatively distinct vowels were compared with two confusible stop consonants. Response times to the vowels were longer than to the consonants. Response times correlated negatively with target phoneme length. In the second, two relatively distinct vowels were compared with their corresponding semivowels. This time, the vowels were detected faster than the semivowels. We conclude that response time differences between vowels and stop consonants in this task may reflect differences between phoneme categories in the variability of tokens, both in the acoustic realisation of targets and in the' representation of targets by subjects.

Abstract

Previous research suggests that bilinguals presented with low and high predictability sentences benefit from semantics in clear but not in conversational speech [1]. In everyday speech, however, many words are not highly predictable. Previous research has shown that native listeners can use also more subtle semantic contextual information [2]. The present study reports two auditory lexical decision experiments investigating to what extent late Asian-English bilinguals benefit from subtle semantic cues in their processing of English unreduced and reduced speech. Our results indicate that these bilinguals are less sensitive to semantic cues than native listeners for both speech registers.

Abstract

Over the years, the field of Language Resources and Technology (LRT) hasdeveloped a tremendous amount of resources and tools. However, there is noready-to-use map that researchers could use to gain a good overview andsteadfast orientation when searching for, say corpora or software tools tosupport their studies. It is rather the case that information is scatteredacross project- or organisation-specific sites, which makes it hard if notimpossible for less-experienced researchers to gather all relevant material.Clearly, the provision of metadata is central to resource and softwareexploration. However, in the LRT field, metadata comes in many forms, tastesand qualities, and therefore substantial harmonization and curation efforts arerequired to provide researchers with metadata-based guidance. To address thisissue a broad alliance of LRT providers (CLARIN, the Linguist List, DOBES,DELAMAN, DFKI, ELRA) have initiated the Virtual Language Observatory portal toprovide a low-barrier, easy-to-follow entry point to language resources andtools; it can be accessed via http://www.clarin.eu/vlo

Abstract

This paper presents an analysis of phoneme durations of emotional speech in two languages: Dutch and Korean. The analyzed corpus of emotional speech has been specifically developed for the purpose of cross-linguistic comparison, and is more balanced than any similar corpus available so far: a) it contains expressions by both Dutch and Korean actors and is based on judgments by both Dutch and Korean listeners; b) the same elicitation technique and recording procedure were used for recordings of both languages; and c) the phonetics of the carrier phrase were constructed to be permissible in both languages. The carefully controlled phonetic content of the carrier phrase allows for analysis of the role of specific phonetic features, such as phoneme duration, in emotional expression in Dutch and Korean. In this study the mutual effect of language and emotion on phoneme duration is presented.

Abstract

In this paper we investigate a computational model of word learning, that is embedded in a cognitively and ecologically plausible framework. Multi-modal stimuli from four different speakers form a varied source of experience. The model incorporates active learning, attention to a communicative setting and clarity of the visual scene. The model's ability to learn associations between speech utterances and visual concepts is evaluated during training to investigate the influence of active learning under conditions of uncertain input. The results show the importance of shared attention in word learning and the model's robustness against noise.

Abstract

This study investigated the perception of American English phonemes by native listeners. Listeners identified either the consonant or the vowel in all possible English CV and VC syllables. The syllables were embedded in multispeaker babble at three signal-to-noise ratios (0 dB, 8 dB, and 16 dB). Effects of syllable position, signal-to-noise ratio, and articulatory features on vowel and consonant identification are discussed. The results constitute the largest source of data that is currently available on phoneme confusion patterns of American English phonemes by native listeners.

Abstract

This study investigated the perception of American English phonemes by native listeners. Listeners identified either the consonant or the vowel in all possible English CV and VC syllables. The syllables were embedded in multispeaker babble at three signalto-noise ratios (0 dB, 8 dB, and 16 dB). Effects of syllable position, signal-to-noise ratio, and articulatory features on vowel and consonant identification are discussed. The results constitute the largest source of data that is currently available on phoneme confusion patterns of American English phonemes by native listeners.

Abstract

In foreign-accented speech, listeners have to handle noticeable deviations from the standard pronunciation of a target language. Three cross-modal priming experiments investigated how short- and long-term experiences with a foreign accent influence word recognition by native listeners. In experiment 1, German-accented words were presented to Dutch listeners who had either extensive or limited prior experience with German-accented Dutch. Accented words either contained a diphthong substitution that deviated acoustically quite largely from the canonical form (huis [hys], "house", pronounced as [hoys]), or that deviated acoustically to a lesser extent (lijst [lst], "list", pronounced as [lst]). The mispronunciations never created lexical ambiguity in Dutch. While long-term experience facilitated word recognition for both types of substitutions, limited experience facilitated recognition only of words with acoustically smaller deviations. In experiment 2, Dutch listeners with limited experience listened to the German speaker for 4 min before participating in the cross-modal priming experiment. The results showed that speaker-specific learning effects for acoustically large deviations can be obtained already after a brief exposure, as long as the exposure contains evidence of the deviations. Experiment 3 investigates whether these short-term adaptation effects for foreign-accented speech are speaker-independent.

Abstract

In the emerging e-Science scenario users should be able to easily combine data resources and tools/services; and machines should automatically be able to trace paths and carry out interpretations. Users who want to participate need to move from a down-load first to a cyberinfrastructure paradigm, thus increasing their dependency on the seamless operation of all components in the Internet. Such a scenario is inherently complex and requires compliance to guidelines and standards to keep it working smoothly. Only a change in our culture of dealing with research data and awareness about the way we do data lifecycle management will lead to success. Since we have so many legacy resources that are not compliant with the required guidelines, since we need to admit obvious problems in particular with standardization in the area of semantics and since it will take much time to establish trust at the side of researchers, the e-Science scenario can only be achieved stepwise which will take much time.

Abstract

In this paper, we describe the core pillars of a large archive oflanguage material recorded worldwide partly about languages that are highly endangered. The bases for the documentation of these languages are audio/video recordings which are then annotated at several linguistic layers. The digital age completely changed the requirements of long-term preservation and it is discussed how the archive met these new challenges. An extensive solution for data replication has been worked out to guarantee bit-stream preservation. Due to an immediate conversion of the incoming data to standards -based formats and checks at upload time lifecycle management of all 50 Terabyte of data is widely simplified. A suitable metadata framework not only allowing users to describe and discover resources, but also allowing them to organize their resources is enabling the management of this amount of resources very efficiently. Finally, it is the Language Archiving Technology software suite which allows users to create, manipulate, access and enrich all archived resources given that they have access permissions.

Abstract

Currently, research infrastructures are being designed and established in manydisciplines since they all suffer from an enormous fragmentation of theirresources and tools. In the domain of language resources and tools the CLARINinitiative has been funded since 2008 to overcome many of the integration andinteroperability hurdles. CLARIN can build on knowledge and work from manyprojects that were carried out during the last years and wants to build stableand robust services that can be used by researchers. Here service centres willplay an important role that have the potential of being persistent and thatadhere to criteria as they have been established by CLARIN. In the last year ofthe so-called preparatory phase these centres are currently developing four usecases that can demonstrate how the various pillars CLARIN has been working oncan be integrated. All four use cases fulfil the criteria of beingcross-national.

Abstract

Language users process utterances by segmenting them into many cognitive units, which vary in their sizes and linguistic levels. Although we can do such unitization/segmentation easily, its cognitive mechanism is still not clear. This paper proposes an unsupervised model, Less-is-Better (LiB), to simulate the human cognitive process with respect to language unitization/segmentation. LiB follows the principle of least effort and aims to build a lexicon which minimizes the number of unit tokens (alleviating the effort of analysis) and number of unit types (alleviating the effort of storage) at the same time on any given corpus. LiB’s workflow is inspired by empirical cognitive phenomena. The design makes the mechanism of LiB cognitively plausible and the computational requirement light-weight. The lexicon generated by LiB performs the best among different types of lexicons (e.g. ground-truth words) both from an information-theoretical view and a cognitive view, which suggests that the LiB lexicon may be a plausible proxy of the mental lexicon.

Abstract

To acquire the meaning of a verb, language learners not only need to find the correct mapping between a specific verb and an action or event in the world, but also infer the underlying relational meaning that the verb encodes. Most verb naming instances in naturalistic contexts are highly ambiguous as many possible actions can be embedded in the same scenario and many possible verbs can be used to describe those actions. To understand whether learners can find the correct verb meaning from referentially ambiguous learning situations, we conducted three experiments using the Human Simulation Paradigm with adult learners. Our results suggest that although finding the right verb meaning from one learning instance is hard, there is a statistical solution to this problem. When provided with multiple verb learning instances all referring to the same verb, learners are able to aggregate information across situations and gradually converge to the correct semantic space. Even in cases where they may not guess the exact target verb, they can still discover the right meaning by guessing a similar verb that is semantically close to the ground truth.

Abstract

The amount of research data in the Humanities is increasing at fastspeed. Metadata helps describing and making accessible this data tointerested researchers within and across institutions. While metadatainteroperability is an issue that is being recognised and addressed,the systematic and user-driven provision of annotations and thelinking together of resources into new organisational layers havereceived much less attention. This paper gives an overview of ourevolving technological eScience environment to support suchfunctionality. It describes two tools, ADDIT and ViCoS, which enableresearchers, rather than archive managers, to organise and reorganiseresearch data to fit their particular needs. The two tools, which areembedded into our institute's existing software landscape, are aninitial step towards an eScience environment that gives our scientistseasy access to (multimodal) research data of their interest, andempowers them to structure, enrich, link together, and share such dataas they wish.