Publications

Abstract

We present multi-modal adversarial autoencoders for recommendation and evaluate them on two different tasks: citation recommendation and subject label recommendation. We analyze the effects of adversarial regularization, sparsity, and different input modalities. By conducting 408 experiments, we show that adversarial regularization consistently improves the performance of autoencoders for recommendation. We demonstrate, however, that the two tasks differ in the semantics of item co-occurrence in the sense that item co-occurrence resembles relatedness in case of citations, yet implies diversity in case of subject labels. Our results reveal that supplying the partial item set as input is only helpful, when item co-occurrence resembles relatedness. When facing a new recommendation task it is therefore crucial to consider the semantics of item co-occurrence for the choice of an appropriate model.

Abstract

The aim of this paper is to explore whether indexing terms for an audiovisual program can be derived from contextual texts automatically. For this we apply natural-language processing techniques to contextual texts of two Dutch TV-programs. We use a Dutch domain thesaurus to derive possible metadata. This possible metadata is ranked by an algorithm which uses the relations of the thesaurus. We evaluate the results by comparing them to human made descriptions.

Abstract

We present a solution to the problem of online speaker/signer diarization - the task of determining "who spoke/signed when?". Our solution is based on the idea that gestural activity (hands and body movement) is highly correlated with uttering activity. This correlation is necessarily true for sign languages and mostly true for spoken languages. The novel part of our solution is the use of motion history images (MHI) as a likelihood measure for probabilistically detecting uttering activities. MHI is an efficient representation of where and how motion occurred for a fixed period of time. We conducted experiments on 4.9 hours of a publicly available dataset (the AMI meeting data) and 1.4 hours of sign language dataset (Kata Kolok data). The best performance obtained is 15.70% for sign language and 31.90% for spoken language (measurements are in DER). These results show that our solution is applicable in real-world applications like video conferences.

Abstract

We demonstrate how the problem of speaker diarization can be solved using both gesture and speaker parametric models. The novelty of our solution is that we approach the speaker diarization problem as a speaker recognition problem after learning speaker models from speech samples corresponding to gestures (the occurrence of gestures indicates the presence of speech and the location of gestures indicates the identity of the speaker). This new approach offers many advantages: comparable state-of-the-art performance, faster computation and more adaptability. In our implementation, parametric models are used to model speakers' voice and their gestures: more specifically, Gaussian mixture models are used to model the voice characteristics of each person and all persons, and gamma distributions are used to model gestural activity based on features extracted from Motion History Images. Tests on 4.24 hours of the AMI meeting data show that our solution makes DER score improvements of 19% on speech-only segments and 4% on all segments including silence (the comparison is with the AMI system).

Abstract

Prior research on language identification focused primarily on text and speech. In this paper, we focus on the visual modality and present a method for identifying sign languages solely from short video samples. The method is trained on unlabelled video data (unsupervised feature learning) and using these features, it is trained to discriminate between six sign languages (supervised learning). We ran experiments on video samples involving 30 signers (running for a total of 6 hours). Using leave-one-signer-out cross-validation, our evaluation on short video samples shows an average best accuracy of 84%. Given that sign languages are under-resourced, unsupervised feature learning techniques are the right tools and our results indicate that this is realistic for sign language identification.

Abstract

This doctoral dissertation investigated the learning of auditory categories by applying insights from child language learning, visual category learning and phonetic categorization by adults. The experiments in chapter 2 concern supervised learning of multidimensional non-speech categories varying in two dimensions: duration and a non speech analogue of formant frequency. In experiment 1, one dimension of variation determined category membership, variation in the other dimension was irrelevant. Listeners quickly learned to categorize according to this distinction. In experiment 2, both dimensions needed to be combined to categorize correctly. Performance was much lower, but most listeners succeeded in this task. However, in a maintenance phase without feedback or distributional information, listeners reverted to a unidimensional solution. In a maintenance phase with distributional information, listeners did use both dimensions correctly, arguing for the importance of distributional information in (auditory) category acquisition. In chapter 3, the listeners had to classify the same categories, but without feedback. In experiment 1, listeners succeeded to discover the relevant dimension of variation (and ignore the irrelevant one) without feedback. Much of this learning was lost in the maintenance phase, especially for the dimension formant frequency. With two relevant dimensions (Experiment 2), listeners were not able to learn to use both dimensions and reverted to a unidimensional solution. Chapter 4 applied the paradigms of chapter 2 and 3 to the learning of speech categories. Spanish native listeners learned Dutch vowel contrast with one relevant dimension of variation. With feedback, learning was swift, although was not well maintained without feedback or distributional information. Without feedback, Spanish listeners reverted to the dimensions best known in their native phonology, formant frequency, even when distributional information pointed to duration. The results are discussed in chapter 5. The implications for models of speech acquisition are discussed.

Abstract

Acquiring the sounds of a language involves learning to recognize distributional patterns present in the input. We show that among adult learners, this distributional learning of auditory categories (which are conceived of here as probability density functions in a multidimensional space) is constrained by the salience of the dimensions that form the axes of this perceptual space. Only with a particular ratio of variation in the perceptual dimensions was category learning driven by the distributional properties of the input.

Abstract

Distributional learning is almost certainly involved in the human acquisition of phonetic categories. Because speech is inherently a multidimensional signal, learning phonetic categories entails multidimensional learning. Yet previous studies of auditory category learning have shown poor maintenance of learned multidimensional categories. Two experiments explored ways to improve maintenance: by increasing the costs associated with applying a unidimensional strategy; by providing additional information about the category structures; and by giving explicit instructions on how to categorize. Only with explicit instructions were categorization strategies maintained in a maintenance phase without supervision or distributional information.

Abstract

What does semantic similarity between two concepts mean? How could we measure it? The way in which semantic similarity is calculated might differ depending on the theoretical notion of semantic representation. In an eye-tracking reading experiment, we investigated whether two widely used semantic similarity measures (based on featural or distributional representations) have distinctive effects on sentence reading times. In other words, we explored whether these measures of semantic similarity differ qualitatively. In addition, we examined whether visually perceived spatial distance interacts with either or both of these measures. Our results showed that the effect of featural and distributional representations on reading times can differ both in direction and in its time course. Moreover, both featural and distributional information interacted with spatial distance, yet in different sentence regions and reading measures. We conclude that featural and distributional representations are distinct components of semantic representation.

Abstract

Recent evidence from eye tracking during reading showed that non-referential spatial distance presented in a visual context can modulate semantic interpretation of similarity relations rapidly and incrementally. In two eye-tracking reading experiments we extended these findings in two important ways; first, we examined whether other semantic domains (social relations) could also be rapidly influenced by spatial distance during sentence comprehension. Second, we aimed to further specify how abstract language is co-indexed with spatial information by varying the syntactic structure of sentences between experiments. Spatial distance rapidly modulated reading times as a function of the social relation expressed by a sentence. Moreover, our findings suggest that abstract language can be co-indexed as soon as critical information becomes available for the reader.

Abstract

Three groups of monolingual listeners, with Standard Chinese, Dutch and Hungarian as their native language, judged pairs of trisyllabic stimuli which differed only in their itch pattern. The segmental structure of the stimuli was made up by the experimenters and presented to subjects as being taken from a little-known language spoken on a South Pacific island. Pitch patterns consisted of a single rise-fall located on or near the second syllable. By and large, listeners selected the stimulus with the higher peak, the later eak, and the higher end rise as the one that signalled a question, regardless of language group. The result is argued to reflect innate, non-linguistic knowledge of the meaning of pitch variation, notably Ohala’s Frequency Code. A significant difference between groups is explained as due to the influence of the mother tongue.

Abstract

This paper investigates the time and space complexity of word order computation in the psycholinguistically motivated grammar formalism of Performance Grammar (PG). In PG, the first stage of syntax assembly yields an unordered tree ('mobile') consisting of a hierarchy of lexical frames (lexically anchored elementary trees). Associated with each lexica l frame is a linearizer—a Finite-State Automaton that locally computes the left-to-right order of the branches of the frame. Linearization takes place after the promotion component may have raised certain constituents (e.g. Wh- or focused phrases) into the domain of lexical frames higher up in the syntactic mobile. We show that the worst-case time and space complexity of analyzing input strings of length n is O(n5) and O(n4), respectively. This result compares favorably with the time complexity of word-order computations in Tree Adjoining Grammar (TAG). A comparison with Head-Driven Phrase Structure Grammar (HPSG) reveals that PG yields a more declarative linearization method, provided that the FSA is rewritten as an equivalent regular expression.

Abstract

Many current sentence generators lack the ability to compute elliptical versions of coordinated clauses in accordance with the rules for Gapping, Forward and Backward Conjunction Reduction, and SGF (Subject Gap in clauses with Finite/ Fronted verb). We describe a module (implemented in JAVA, with German and Dutch as target languages) that takes non-elliptical coordinated clauses as input and returns all reduced versions licensed by coordinative ellipsis. It is loosely based on a new psycholinguistic theory of coordinative ellipsis proposed by Kempen. In this theory, coordinative ellipsis is not supposed to result from the application of declarative grammar rules for clause formation but from a procedural component that interacts with the sentence generator and may block the overt expression of certain constituents.

Abstract

We describe a generation-oriented workbench for the Performance Grammar (PG) formalism, highlighting the treatment of certain word order and movement constraints in Dutch and German. PG enables a simple and uniform treatment of a heterogeneous collection of linear order phenomena in the domain of verb constructions (variably known as Cross-serial Dependencies, Verb Raising, Clause Union, Extraposition, Third Construction, Particle Hopping, etc.). The central data structures enabling this feature are clausal “topologies”: one-dimensional arrays associated with clauses, whose cells (“slots”) provide landing sites for the constituents of the clause. Movement operations are enabled by unification of lateral slots of topologies at adjacent levels of the clause hierarchy. The PGW generator assists the grammar developer in testing whether the implemented syntactic knowledge allows all and only the well-formed permutations of constituents.

Abstract

Syntactic parsers and generators need highquality grammars of coordination and coordinate ellipsis—structures that occur very frequently but are much less well understood theoretically than many other domains of grammar. Modern grammars of coordinate ellipsis are based nearly exclusively on linguistic judgments (intuitions). The extent to which grammar rules based on this type of empirical evidence generate all and only the structures in text corpora, is unknown. As part of a project on the development of a grammar and a generator for coordinate ellipsis in German, we undertook an extensive exploration of the TIGER treebank—a syntactically annotated corpus of about 50,000 newspaper sentences. We report (1) frequency data for the various patterns of coordinate ellipsis, and (2) several rarely (but regularly) occurring ‘fringe deviations’ from the intuition-based rules for several ellipsis types. This information can help improve parser and generator performance.

Abstract

The potential of sentence generators as engines in Intelligent Computer-Assisted Language Learning and teaching (ICALL) software has hardly been explored. We sketch the prototype of COMPASS, a system that supports integrated writing and grammar curricula for 10 to 14 year old elementary or secondary schoolers. The system enables first- or second-language teachers to design controlled writing exercises, in particular of the “sentence combining” variety. The system includes facilities for error diagnosis and on-line feedback. Syntactic structures built by students or system can be displayed as easily understood phrase-structure or dependency trees, adapted to the student’s level of grammatical knowledge. The heart of the system is a specially designed generator capable of lexically guided sentence generation, of generating syntactic paraphrases, and displaying syntactic structures visually.

Abstract

This thesis elaborates on a methodological approach to reliably infer cognitive preferences in an extinct evolutionary ancestor of modern humans. In attempts to understand cognitive evolution, humans have been compared to capuchin monkeys, tamarins, and chimpanzees to name but a few. But comparisons between humans and one other, maybe even distantly related primate, as interesting as they might be, will not tell us anything about an evolutionary ancestor to humans. To put it bluntly: None of the living primates, not even chimpanzees, are a human ancestor. With that in mind, we can still use a comparative approach to gain information about our evolutionary ancestors, as long as we are careful about whom we compare with whom. If a certain trait exists in all genera of a phylogenetic clade, it was most likely present in their common ancestor. The great apes are such a clade (Pongo, Gorilla, Pan and Homo). It follows that, if members of all great ape genera shared a particular cognitive preference or ability, it is most likely part of the evolutionary inheritance of the clade at least ever since their last common ancestor, and therefore also an evolutionarily old, inherited cognitive default in humans. This thesis contains studies comparing all 4 extant Hominid genera, including humans of 4 different age-groups and 2 different cultures. Results show that all great apes do indeed share some cognitive preferences, which they most likely inherited from an evolutionary ancestor. Additionally, human cognitive preferences can change away from such an inherited predisposition given ontogenetic factors, and are at least in part variably adaptable to cultural circumstance.

Abstract

Longitudinally collected VOT data from an early English-Italian bilingual who became increasingly English-dominant was analyzed. Stops in English were always produced with significantly longer VOT than in Italian. However, the speaker did not show any significant change in the VOT production in either language over time, despite the clear dominance of English in his every day language use later in his life. The results indicate that – unlike L2 learners – early bilinguals may remain unaffected by language use with respect to phonetic realization.

Abstract

This paper reports on findings from an elicited production task with German 5-year-old children, investigating their use of intonation to mark information status of discourse referents. In line with findings for adults, new referents were preferably marked by H* and L+H*; textually given referents were mainly deaccented. Accessible referents (whose first mentions were less recent) were mostly accented, and predominantly also realised with H* and L+H*, showing children’s sensitivity to recency of mention. No evidence for the consistent use of a special ‘accessibility accent’ H+L* (as has been proposed for adult German) was found.

Abstract

The use of virtual reality (VR) as a methodological tool is
becoming increasingly popular in behavioural research due
to its seemingly limitless possibilities. This new method has
not been used frequently in the field of psycholinguistics,
however, possibly due to the assumption that humancomputer
interaction does not accurately reflect human-human
interaction. In the current study we compare participants’
language behaviour in a syntactic priming task with human
versus avatar partners. Our study shows comparable priming
effects between human and avatar partners (Human: 12.3%;
Avatar: 12.6% for passive sentences) suggesting that VR is a
valid platform for conducting language research and studying
dialogue interactions.

Abstract

In this paper, we show how acoustic variance within lexical tones in disyllabic Mandarin Chinese pseudowords affects discrimination abilities in both native and non-native speakers of Mandarin Chinese. Within-category acoustic variance did not hinder native speakers in discriminating between lexical tones, whereas it precludes Dutch native speakers from reaching native level performance. Furthermore, the influence of acoustic variance was not uniform but asymmetric, dependent on the presentation order of the lexical tones to be discriminated. An exploratory analysis using an active adaptive oddball paradigm was used to quantify the extent of the perceptual asymmetry. We discuss two possible mechanisms underlying this asymmetry and propose possible paradigms to investigate these mechanisms

Abstract

What makes some words harder to learn than others in a second language? Although some robust factors have been identified based on small scale experimental studies, many relevant factors are difficult to study in such experiments due to the amount of data necessary to test them. Here, we investigate what factors affect the ease of learning of a word in a second language using a large data set of users learning English as a second language through the Duolingo mobile app. In a regression analysis, we test and confirm the well-studied effect of cognate status on word learning accuracy. Furthermore, we find significant effects for both cross-linguistic semantic alignment and English semantic density, two novel predictors derived from large scale distributional models of lexical semantics. Finally, we provide data on several other psycholinguistically plausible word level predictors. We conclude with a discussion of the limits, benefits and future research potential of using big data for investigating second language learning.

Abstract

Thesaurus alignment is important for efficient access to heterogeneous Cultural Heritage data. Current ontology alignment techniques provide solutions, but with limited value in practice, because the requirements from usage scenarios are rarely taken in account. In this paper, we start from particular requirements for book re-indexing and investigate possible ways of developing, deploying and evaluating thesaurus alignment techniques in this context. We then compare different aspects of this scenario with others from a more general perspective.

Abstract

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

Abstract

In this study we investigated to what extent a meaningful sentence context facilitates spoken word processing in young and older listeners if listening is made taxing by time-compressing the speech. Even though elderly listeners have been shown to benefit more from sentence context in difficult listening conditions than young listeners, time compression of speech may interfere with semantic comprehension, particularly in older listeners because of cognitive slowing. The results of a target detection experiment showed that, unlike young listeners who showed facilitation by context at both rates, elderly listeners showed context facilitation at the intermediate, but not at the fastest rate. This suggests that semantic interpretation lags behind target identification.

Abstract

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

Abstract

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

Abstract

Listeners use lexical knowledge to adjust their prelexical representations of speech sounds in response to the idiosyncratic pronunciations of particular speakers. We used an exposure-test paradigm to investigate whether this type of perceptual learning transfers across syllabic positions. No significant learning effect was found in Experiment 1, where exposure sounds were onsets and test sounds were codas. Experiments 2-4 showed that there was no learning even when both exposure and test sounds were onsets. But a trend was found when exposure sounds were codas and test sounds were onsets (Experiment 5). This trend was smaller than the robust effect previously found for the coda-to-coda case. These findings suggest that knowledge about idiosyncratic pronunciations may be position specific: Knowledge about how a speaker produces sounds in one position, if it can be acquired at all, influences perception of sounds in that position more strongly than of sounds in another position.

Abstract

Words repeated in the same voice are better recognized than when they are repeated in a different voice. Such findings have been taken as evidence for the storage of talker-specific lexical episodes. But results on perceptual learning suggest that talker-specific adjustments concern sublexical representations. This study thus investigates whether voice-specific repetition effects in auditory lexical decision are lexical or sublexical. The same critical set of items in Block 2 were, depending on materials in Block 1, either same-voice or different-voice word repetitions, new words comprising re-orderings of phonemes used in the same voice in Block 1, or new words with previously unused phonemes. Results show a benefit for words repeated by the same talker, and a smaller benefit for words consisting of phonemes repeated by the same talker. Talker-specific information thus appears to influence word recognition at multiple representational levels.

Abstract

Listeners use suprasegmental auditory lexical stress information to resolve the competition words engage in during spoken-word recognition. The present study investigated whether (a) visual speech provides lexical stress information, and, more importantly, (b) whether this visual lexical stress information is used to resolve lexical competition. Dutch word pairs that differ in the lexical stress realization of their first two syllables, but not segmentally (e.g., 'OCtopus' and 'okTOber'; capitals marking primary stress) served as auditory-only, visual-only, and audiovisual speech primes. These primes either matched (e.g., 'OCto-'), mismatched (e.g., 'okTO-'), or were unrelated to (e.g., 'maCHI-') a subsequent printed target (octopus), which participants had to make a lexical decision to. To the degree that visual speech contains lexical stress information, lexical decisions to printed targets should be modulated through the addition of visual speech. Results show, however, no evidence for a role of visual lexical stress information in audiovisual spoken-word recognition.

Abstract

The present paper describes the development of the languagesindanger.eu interactive website as an example of including multimedia language resources to disseminate knowledge and create educational material on less-resourced languages. The website is a product of INNET (Innovative networking in infrastructure for endangered languages), European FP7 project. Its main functions can be summarized as related to the three following areas: (1) raising students' awareness of language endangerment and arouse their interest in linguistic diversity, language maintenance and language documentation; (2) informing both students and teachers about these topics and show ways how they can enlarge their knowledge further with a special emphasis on information about language archives; (3) helping teachers include these topics into their classes. The website has been localized into five language versions with the intention to be accessible to both scientific and non-scientific communities such as (primarily) secondary school teachers and students, beginning university students of linguistics, journalists, the interested public, and also members of speech communities who speak minority languages

Abstract

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

Abstract

The previous literature has suggested that the hand movement in co-speech gestures and signs consists of a series of phases with qualitatively different dynamic characteristics. In this paper, we propose a syntagmatic rule system for movement phases that applies to both co-speech gestures and signs. Descriptive criteria for the rule system were developed for the analysis video-recorded continuous production of signs and gesture. It involves segmenting a stream of body movement into phases and identifying different phase types. Two human coders used the criteria to analyze signs and cospeech gestures that are produced in natural discourse. It was found that the criteria yielded good inter-coder reliability. These criteria can be used for the technology of automatic recognition of signs and co-speech gestures in order to segment continuous production and identify the potentially meaningbearing phase.

Abstract

The VALID Data Archive is an open multimedia data archive (under construction) with data from speakers suffering from language impairments. We report on a pilot project in the CLARIN-NL framework in which five data resources were curated. For all data sets concerned, written informed consent from the participants or their caretakers has been obtained. All materials were anonymized. The audio files were converted into wav (linear PCM) files and the transcriptions into CHAT or ELAN format. Research data that consisted of test, SPSS and Excel files were documented and converted into CSV files. All data sets obtained appropriate CMDI metadata files. A new CMDI metadata profile for this type of data resources was established and care was taken that ISOcat metadata categories were used to optimize interoperability. After curation all data are deposited at the Max Planck Institute for Psycholinguistics Nijmegen where persistent identifiers are linked to all resources. The content of the transcriptions in CHAT and plain text format can be searched with the TROVA search engine

Abstract

Word segmentation, or detecting word boundaries in continuous speech, is not an easy task. Spoken language does not contain silences to indicate word boundaries and words partly overlap due to coarticalution. Still, adults listening to their native language perceive speech as individual words. They are able to combine different distributional cues in the language, such as the statistical distribution of sounds and metrical cues, with lexical information, to efficiently detect word boundaries. Infants in the first year of life do not command these cues. However, already between seven and ten months of age, before they know word meaning, infants learn to segment words from speech. This important step in language acquisition is the topic of this dissertation. In chapter 2, the first Event Related Brain Potential (ERP) study on word segmentation in Dutch ten-month-olds is discussed. The results show that ten-month-olds can already segment words with a strong-weak stress pattern from speech and they need roughly the first half of a word to do so. Chapter 3 deals with segmentation of words beginning with a weak syllable, as a considerable number of words in Dutch do not follow the predominant strong-weak stress pattern. The results show that ten-month-olds still largely rely on the strong syllable in the language, and do not show an ERP response to the initial weak syllable. In chapter 4, seven-month-old infants' segmentation of strong-weak words was studied. An ERP response was found to strong-weak words presented in sentences. However, a behavioral response was not found in an additional Headturn Preference Procedure study. There results suggest that the ERP response is a precursor to the behavioral response that infants show at a later age.

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

The present study investigates the influence of prosodic structure on the fine-grained phonetic details of German plosives which also cue the phonological fortis-lenis contrast. Closure durations were found to be longer at higher prosodic boundaries. There was also less glottal vibration in lenis plosives at higher prosodic boundaries. Voice onset time in lenis plosives was not affected by prosody. In contrast, for the fortis plosives VOT decreased at higher boundaries, as did the maximal intensity of the release. These results demonstrate that the effects of prosody on different phonetic cues can go into opposite directions, but are overall constrained by the need to maintain phonological contrasts. While prosodic effects on some cues are compatible with a ‘fortition’ account of prosodic strengthening or with a general feature enhancement explanation, the effects on others enhance paradigmatic contrasts only within a given prosodic position.

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

In this study, we explored methods for linking Chinese and English sense inventories using two opposing approaches: creating links (1) bottom-up: by starting at the finer-grained sense level then proceeding to the verb subcategorization frames and (2) top-down: by starting directly with the more coarse-grained frame levels. The sense inventories for linking include pre-existing corpora, such as English Propbank (Palmer, Gildea, and Kingsbury, 2005), Chinese Propbank (Xue and Palmer, 2004) and English WordNet (Fellbaum, 1998) and newly created corpora, the English and Chinese Sense Inventories from DARPA-GALE OntoNotes. In the linking task, we selected a group of highly frequent and polysemous communication verbs, including say, ask, talk, and speak in English, and shuo, biao-shi, jiang, and wen in Chinese. We found that with the bottom-up method, although speakers of both languages agreed on the links between senses, the subcategorization frames of the corresponding senses did not match consistently. With the top-down method, if the verb frames match in both languages, their senses line up more quickly to each other. The results indicate that the top-down method is more promising in linking English and Chinese sense inventories.

Abstract

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

Abstract

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

Abstract

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

Abstract

Evolution and changes of all modern languages is a wellknown 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 rich heritage, and to carry out linguistic research, 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. This is the scope of the AVATecH project presented in this article

Abstract

People's language is shaped by the input from the environment. The environment, however, offers a range of linguistic inputs that differ in their reliability. We test whether listeners accordingly weigh input from sources that differ in reliability differently. Using a perceptual learning paradigm, we show that listeners adjust their representations according to linguistic input provided by native but not by non-native speakers. This is despite the fact that listeners are able to learn the characteristics of the speech of both speakers. These results provide evidence for a disassociation between adaptation to the characteristic of specific speakers and adjustment of linguistic representations in general based on these learned characteristics. This study also has implications for theories of language change. In particular, it cast doubts on the hypothesis that a large proportion of non-native speakers in a community can bring about linguistic changes

Abstract

This study investigates prosodic marking of focus in Bai, a Sino-Tibetan language spoken in the Southwest of China, by adopting a semi-spontaneous experimental approach. Our data show that Bai speakers increase the duration of the focused constituent and reduce the duration of the post-focus constituent to encode focus. However, duration is not used in Bai to distinguish focus types differing in size and contrastivity. Further, pitch plays no role in signaling focus and differentiating focus types. The results thus suggest that Bai uses prosody to mark focus, but to a lesser extent, compared to Mandarin Chinese, with which Bai has been in close contact for centuries, and Cantonese, to which Bai is similar in the tonal system, although Bai is similar to Cantonese in its reliance on duration in prosodic focus marking.

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

Two Siberian languages, Tundra Nenets and Tundra Yukaghir, do not obey strong island constraints in questioning: any sub-constituent of a relative or adverbial clause can be questioned. We argue that this has to do with how focusing works in these languages. The focused sub-constituent remains in situ, but there is abundant morphosyntactic evidence that the focus feature is passed up to the head of the clause. The result is the formation of a complex focus structure in which both the head and non head daughter are overtly marked as focus, and they are interpreted as a pairwise list such that the focus background is applicable to this list, but not to other alternative lists

Abstract

The results of a word-spotting experiment are presented in which Dutch listeners tried to spot different types of bisyllabic Dutch words embedded in different types of nonsense contexts. Embedded verbs were not reliably harder to spot than embedded nouns; this suggests that nouns and verbs are recognised via the same basic processes. Iambic words were no harder to spot than trochaic words, suggesting that trochaic words are not in principle easier to recognise than iambic words. Words were harder to spot in consonantal contexts (i.e., contexts which themselves could not be words) than in longer contexts which contained at least one vowel (i.e., contexts which, though not words, were possible words of Dutch). A control experiment showed that this difference was not due to acoustic differences between the words in each context. The results support the claim that spoken-word recognition is sensitive to the viability of sound sequences as possible words.

Abstract

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

Abstract

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

Abstract

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

Listeners use lexical knowledge to judge what speech sounds they heard. I investigated whether such lexical influences are truly top-down or just reflect a merging of perceptual and lexical constraints. This is achieved by testing whether the lexically determined identity of a phone exerts the appropriate context effects on surrounding phones. The current investigations focuses on compensation for coarticulation in vowel-fricative sequences, where the presence of a rounded vowel (/y/ rather than /i/) leads fricatives to be perceived as /s/ rather than //. This results was consistently found in all three experiments. A vowel was also more likely to be perceived as rounded /y/ if that lead listeners to be perceive words rather than nonwords (Dutch: meny, English id. vs. meni nonword). This lexical influence on the perception of the vowel had, however, no consistent influence on the perception of following fricative.