Publications

Abstract

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

Abstract

In German, word-initial lax fricatives may be produced with substantially reduced glottal vibration after voiceless obstruents. This assimilation occurs more frequently and to a larger extent across prosodic word boundaries than across phrase boundaries. Assimilatory devoicing makes the fricatives more similar to their tense counterparts and could thus hinder word recognition. The present study investigates how listeners cope with assimilatory devoicing. Results of a cross-modal priming experiment indicate that listeners compensate for assimilation in appropriate contexts. Prosodic structure moderates compensation for assimilation: Compensation occurs especially after phrase boundaries, where devoiced fricatives are sufficiently long to be confused with their tense counterparts.

Abstract

Prosodic structure has long been known to constrain phonological processes [1]. More recently, it has also been recognized as a source of fine-grained phonetic variation of speech sounds. In particular, segments in domain-initial position undergo prosodic strengthening [2, 3], which also implies more resistance to coarticulation in higher prosodic domains [5]. The present study investigates the combined effects of prosodic strengthening and assimilatory devoicing on word-initial fricatives in German, the functional implication of both processes for cues to the fortis-lenis contrast, and the influence of prosodic structure on listeners’ compensation for assimilation. Results indicate that 1. Prosodic structure modulates duration and the degree of assimilatory devoicing, 2. Phonological contrasts are maintained by speakers, but differ in phonetic detail across prosodic domains, and 3. Compensation for assimilation in perception is moderated by prosodic structure and lexical constraints.

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

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

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

This paper presents an analysis of semantic association norms for German nouns. In contrast to prior studies, we not only collected associations elicited by written representations of target objects but also by their pictorial representations. In a first analysis, we identified systematic differences in the type and distribution of associate responses for the two presentation forms. In a second analysis, we applied a soft cluster analysis to the collected target-response pairs. We subsequently used the clustering to predict noun ambiguity and to discriminate senses in our target nouns.

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

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

The present doctoral thesis investigates the temporal characteristics of the retrieval of semantic and syntactic word properties in language comprehension. In particular, an attempt is made to assess the retrieval order of semantic category and grammatical gender information, using the lateralized readiness potential and the inhibition-related N2 effect. Chapter 1 contains a general introduction. Chapter 2 reports an experiment that employs the two-choice go/nogo task in combination with EEG recordings to establish the retrieval order of semantic category and grammatical gender for written words presented in isolation. The results point to a time course where semantic information becomes available before syntactic information. Chapter 3 focuses on the retrieval of grammatical gender. In order to examine whether gender retrieval can be speeded up by context, nouns are presented in gender congruent and gender incongruent prime-target pairs and reaction times for gender decisions are measured. For stimulus onset asynchronies of 100 ms and 0 ms, gender congruent pairs show faster responses than incongruent ones, whereas there is no effect of gender congruity for a stimulus onset asynchrony of 300 ms. A simulation with a localist computational model that implements competition between gender representations (WEAVER; Roelofs, 1992) is able to capture these findings. In chapter 4, the gender congruency manipulation is transferred to another ERP experiment with the two-choice go/nogo task. As the time course of gender retrieval is altered through primes, the order relative to semantic category retrieval is assessed again. The results indicate that with gender congruent primes, grammatical gender becomes available before semantic category. Such a reversal of retrieval order, as compared to chapter 2, implies a parallel rather than a serial discrete arrangement of the retrieval processes, since the latter variant precludes changes in retrieval order. Finally, chapter 5 offers a summary and general discussion of the main findings.

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 dissertation documents the emergence of a new language, Light Warlpiri, in the multilingual community of Lajamanu in northern Australia. It then examines the acquisition of Light Warlpiri language, and of the heritage language, Lajamanu Warlpiri, by children. Light Warlpiri has arisen from contact between Lajamanu Warlpiri (a Pama-Nyungan language), Kriol (an English-based creole), and varieties of English. It is a Mixed Language, meaning that none of its source languages can be considered to be the sole parent language. Most verbs and the verbal morphology are from Aboriginal English or Kriol, while most nouns and the nominal morphology are from Warlpiri. The language input to children is complex. Adults older than about thirty speak Lajamanu Warlpiri and code-switch into Aboriginal English or Kriol. Younger adults, the parents of the current cohort of children, speak Light Warlpiri and code-switch into Lajamanu Warlpiri and into Aboriginal English or Kriol. Lajamanu Warlpiri and Light Warlpiri, the two main input languages to children, both indicate A arguments with ergative case-marking (and they share one allomorph of the marker), but Lajamanu Warlpiri includes the marker much more consistently than Light Warlpiri. Word order is variable in both languages. Children learn both languages from birth, but they target Light Warlpiri as the language of their everyday interactions, and they speak it almost exclusively until four to six years of age. Adults and children show similar patterns of ergative marking and word order in Light Warlpiri. But differences between age groups are found in ergative marking in Lajamanu Warlpiri - for the oldest group of adults, ergative marking is obligatory, but for younger adults and children, it is not. Determining when children differentiate between two input languages has been a major goal in the study of bilingual acquisition. The two languages in this study share lexical and grammatical properties, making distinctions between them quite subtle. Both adults and children distribute ergative marking differently in the two languages, but show similar word order patterns in both. However the children show a stronger correlation between ergative marking and word order patterns than do the adults, suggesting that they are spearheading processes of language change. In their comprehension of sentences in both Lajamanu Warlpiri and Light Warlpiri, adults use a case-marking strategy to identify the A argument (i.e. N+erg = A argument, N-erg = O argument). The children are not adult-like in using this strategy at age 5, when they also used a word order strategy, but they gradually move towards being adult-like with increased age.

Abstract

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

Abstract

In this paper we try to contribute to the body of knowledge about the acquisition of English epistemic modal verbs (e.g. Mary may/has to be at school). Semantically, these verbs encode possibility or necessity with respect to available evidence. Pragmatically, the use of epistemic modals often gives rise to scalar conversational inferences (Mary may be at school -> Mary doesn’t have to be at school). The acquisition of epistemic modals is challenging for children on both these levels. In this paper, we present findings from two studies which were conducted with 5-year-old children and adults. Our findings, unlike previous work, show that 5-yr-olds have mastered epistemic modal semantics, including the notions of necessity and possibility. However, they are still in the process of acquiring epistemic modal pragmatics.

Abstract

En este artículo se desarrolla un método automático de segmentación de fonemas no supervisado. Este método utiliza el algoritmo de agrupación de máximo margen [1] para realizar segmentación de fonemas sobre habla continua sin necesidad de información a priori para el entrenamiento del sistema.

Abstract

This study investigates whether the acoustic durations of derivational affixes in Dutch are affected by the frequency of the word they occur in. In a word naming experiment, subjects were presented with a large number of words containing one of the affixes ge-, ver-, ont, or -lijk. Their responses were recorded on DAT tapes, and the durations of the affixes were measured using Automatic Speech Recognition technology. To investigate whether frequency also affected durations when speech rate was high, the presentation rate of the stimuli was varied. The results show that a higher frequency of the word as a whole led to shorter acoustic realizations for all affixes. Furthermore, affixes became shorter as the presentation rate of the stimuli increased. There was no interaction between word frequency and presentation rate, suggesting that the frequency effect also applies in situations in which the speed of articulation is very high.

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

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

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

Abstract

The ultimate goal of our research is to develop a computational model of human speech recognition that is able to capture the effects of fine-grained acoustic variation on speech recognition behaviour. As part of this work we are investigating automatic feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. In the experiments reported here, we compared support vector machines (SVMs) with multilayer perceptrons (MLPs). MLPs have been widely (and rather successfully) used for the task of multi-value articulatory feature classification, while (to the best of our knowledge) SVMs have not. This paper compares the performances of the two classifiers and analyses the results in order to better understand the articulatory representations. It was found that the MLPs outperformed the SVMs, but it is concluded that both classifiers exhibit similar behaviour in terms of patterns of errors.

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

Functional Magnetic Resonance Imaging (fMRI) and Electropencephalography (EEG) are the two techniques that are most often used to study the working brain. With the first technique we use the MRI machine to measure where in the brain the supply of oxygenated blood increases as result of an increased neural activity with a high precision. The temporal resolution of this measure however is limited to a few seconds. With EEG we measure the electrical activity of the brain with millisecond precision by placing electrodes on the skin of the head. We can think of the EEG signal as a signal that consists of multiple superimposed frequencies that vary their strength over time and when performing a cognitive task. Since we measure EEG at the level of the scalp, it is difficult to know where in the brain the signals exactly originate from. For about a decade we are able to measure fMRI and EEG at the same time, which possibly enables us to combine the superior spatial resolution of fMRI with the superior temporal resolution of EEG. To make this possible, we need to understand how the EEG signal is related to the fMRI signal, which is the central theme of this thesis. The main finding in this thesis is that increases in the strength of EEG frequencies below 30 Hz are related to a decrease in the fMRI signal strength, while increases in the strength of frequencies above 40 Hz is related to an increase in the strength of the fMRI signal. Changes in the strength of the low EEG frequencies are however are not coupled to changes in high frequencies. Changes in the strength of low and high EEG frequencies therefore contribute independently to changes in the fMRI signal.

Abstract

This presentation will address aspects of the expression of emotion in non-verbal vocal behaviour, specifically attempting to determine the roles of both positive and negative emotions, their acoustic bases, and the extent to which these are recognized in non-Western cultures.

Abstract

The present study examined how the updating, inhibiting, and shifting abilities underlying executive control influence spoken noun-phrase production. Previous studies provided evidence that updating and inhibiting, but not shifting, influence picture naming response time (RT). However, little is known about the role of executive control in more complex forms of language production like generating phrases. We assessed noun-phrase production using picture description and a picture-word interference procedure. We measured picture description RT to assess length, distractor, and switch effects, which were assumed to reflect, respectively, the updating, inhibiting, and shifting abilities of adult participants. Moreover, for each participant we obtained scores on executive control tasks that measured verbal and nonverbal updating, nonverbal inhibiting, and nonverbal shifting. We found that both verbal and nonverbal updating scores correlated with the overall mean picture description RTs. Furthermore, the length effect in the RTs correlated with verbal but not nonverbal updating scores, while the distractor effect correlated with inhibiting scores. We did not find a correlation between the switch effect in the mean RTs and the shifting scores. However, the shifting scores correlated with the switch effect in the normal part of the underlying RT distribution. These results suggest that updating, inhibiting, and shifting each influence the speed of phrase production, thereby demonstrating a contribution of all three executive control abilities to language production.

Abstract

Op een gemiddelde dag luisteren mensen naar spraak van heel veel verschillende mensen. Die hebben allemaal een ander stemgeluid, waardoor de woorden die zij uitspreken verschillend klinken. Luisteraars hebben daar echter weinig hinder van. Hoe is het mogelijk dat luisteraars zich zo gemakkelijk kunnen aanpassen aan verschillende sprekers? Matthias Sjerps onderzocht in zijn proefschrift een cognitief mechanisme dat luisteraars helpt om zich aan te passen aan de karakteristieken van verschillende sprekers. Hierbij maakt een luisteraar gebruik van informatie in de context. Dit mechanisme blijkt vroeg in de spraakverwerking plaats te vinden. Bovendien beïnvloedt dit mechanisme ook de perceptie van andere geluiden dan spraak. Dit laat zien dat het een zeer breed en algemeen perceptueel mechanisme betreft. Contexteffecten bleken echter sterker voor spraakgeluiden dan voor andere geluiden. Dit suggereert dat het onderzochte mechanisme, ook al is het algemeen en breed toepasbaar, versterkt kan worden door blootstelling aan taal.

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 classification of texts and pieces of texts uses the occurrence of, combinations of, words as an important indicator. Not every word or each combination of words gives a clear indication of the classification of a piece of text. Research has been done on methods that select some words or combinations of words that are more indicative of the type of a piece of text. These words or combinations of words are selected from the words and word-groups as they occur in the texts. These more indicative words or combinations of words we call ¿cue-phrases¿. The goal of these methods is to select the most indicative cue-phrases first. The collection of selected words and/or combinations thereof can then be used for training the classification system. To test these selection methods, a number of experiments has been done on a corpus containing cookbook recipes and on a corpus of four-participant meetings. To perform these experiments, a computer program was written. On the recipe corpus we looked at classifying the sentences into different types. Some examples of these types include ¿requirement¿ and ¿instruction¿. On the four-person meeting corpus we tried to learn, using only lexical features, whether a sentence is addressed to an individual or a group. The experiments on the recipe corpus produced good results that showed that, a number of, the used cue-phrase selection methods are suitable for feature selection. The experiments on the four-person meeting corpus where less successful in terms of performance off the classification task. We did see comparable patterns in selection methods, and considering the results of Jovanovic we can conclude that different features are needed for this particular classification task. One of the original goals was to look at ¿addressee¿ in discussions. Are sentences more often addressed to individuals inside discussions compared to outside discussions? However, in order to be able to accomplish this, we must first identify the segments of the text that are discussions. It proved hard to come to a reliable specification of discussions, and our initial definition wasn¿t sufficient.

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 describes ongoing research aiming at the description of variation in speech as represented by asynchronous articulatory features. We will first illustrate how distances in the articulatory feature space can be used for event detection along speech trajectories in this space. The temporal structure imposed by the cosine distance in articulatory feature space coincides to a large extent with the manual segmentation on phone level. The analysis also indicates that the articulatory feature representation provides better such alignments than the MFCC representation does. Secondly, we will present first results that indicate that articulatory features can be used to probe for acoustic differences in the onsets of Dutch singulars and plurals.

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 builds on previous work that aims at unraveling the structure of the speech signal by means of using probabilistic representations. The context of this work is a multi-pass speech recognition system in which a phone lattice is created and used as a basis for a lexical search in which symbolic mismatches are allowed at certain costs. The focus is on the optimization of the costs of phone insertions, deletions and substitutions that are used in the lexical decoding pass. Two optimization approaches are presented, one related to a multi-pass computational model for human speech recognition, the other based on a decoding in which Bayes’ risks are minimized. In the final section, the advantages of these optimization methods are discussed and compared.

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

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

Spraakklanken, lettergrepen en woorden worden vaak minder duidelijk uitgesproken in spontane conversaties dan in formelere spreekstijlen. Dit proefschrift presenteert onderzoek naar spraakreductie in spontaan Frans en Spaans. Naar deze talen is tot nu toe weinig spraakreductieonderzoek gedaan. Er worden twee nieuwe grote corpora met spontaan Frans en Spaans beschreven. Op basis van deze corpora heb ik enkele onderzoeken gedaan waarin ik de volgende belangrijke conclusies heb getrokken. Allereerst vond ik dat akoestische data van spontane spraak waardevolle informatie kan geven over de vraag of specifieke reductiefenomenen categoriaal of continu zijn. Verder vond ik, in tegenstelling tot onderzoek naar Germaanse talen, slechts gedeeltelijk bewijs dat spraakreductie in Romaanse talen als het Frans en het Spaans beïnvloed wordt door de eigenschappen en voorspelbaarheid van het woord. Ten derde vond ik door spontaan Frans en Spaans te vergelijken dat spraakreductie tussen talen meer kan verschillen dan je zou verwachten op basis van laboratoriumonderzoek