Publications

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

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

Different linguistic modalities (speech or sign) offer different levels at which signals can iconically represent the world. One hypothesis argues that this iconicity has an effect on how linguistic structure emerges. However, exactly how and why these effects might come about is in need of empirical investigation. In this contribution, we present a signal creation experiment in which both the signalling space and the meaning space are manipulated so that different levels and types of iconicity are available between the signals and meanings. Signals are produced using an infrared sensor that detects the hand position of participants to generate auditory feedback. We find evidence that iconicity may be maladaptive for the discrimination of created signals. Further, we implemented Hidden Markov Models to characterise the structure within signals, which was also used to inform a metric for iconicity.

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

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

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

Frequent and predictable words are generally pronounced with less effort and are therefore acoustically more reduced than less frequent or unpredictable words. Local predictability can be operationalised by Transitional Probability (TP), which indicates how likely a word is to occur given its immediate context. We investigated whether and how probabilistic reduction effects on word durations change with adult age when reading aloud content words embedded in sentences. The results showed equally large frequency effects on verb and noun durations for both younger (Mage = 20 years) and older (Mage = 68 years) adults. Backward TP also affected word duration for younger and older adults alike. ForwardTP, however, had no significant effect on word duration in either age group. Our results resemble earlier findings of more robust BackwardTP effects compared to ForwardTP effects. Furthermore, unlike often reported decline in predictive processing with aging, probabilistic reduction effects remain stable across adulthood.

Abstract

It has been observed by several researchers that the Khoisan palate tends to lack a prominent alveolar ridge. A preliminary biomechanical model of click production was created to examine if these sounds might be subject to an anatomical bias associated with alveolar ridge size. Results suggest the bias is plausible, taking the form of decreased articulatory effort and improved volume change characteristics, however, further modelling and experimental research is required to solidify the claim.

Abstract

This paper investigated the learnability and generalizability of French schwa alternation by Dutch low-proficiency second language learners. We trained 40 participants on 24 new schwa words by exposing them equally often to the reduced and full forms of these words. We then assessed participants' accuracy and reaction times to these newly learnt words as well as 24 previously encountered schwa words with an auditory lexical decision task. Our results show learning of the new words in both forms. This suggests that lack of exposure is probably the main cause of learners' difficulties with reduced forms. Nevertheless, the full forms were slightly better recognized than the reduced ones, possibly due to phonetic and phonological properties of the reduced forms. We also observed no generalization to previously encountered words, suggesting that our participants stored both of the learnt word forms and did not create a rule that applies to all schwa words.

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

In speech, words are often reduced rather than fully pronounced (e.g., (/ˈsʌmri/ for /ˈsʌməri/, summary). Non-native listeners may have problems in processing these reduced forms, because they have encountered them less often. This paper addresses the question whether this also holds for highly proficient non-natives and for words with similar forms and meanings in the non-natives' mother tongue (i.e., cognates). In an English auditory lexical decision task, natives and highly proficient Dutch non-natives of English listened to cognates and non-cognates that were presented in full or without their post-stress schwa. The data show that highly proficient learners are affected by reduction as much as native speakers. Nevertheless, the two listener groups appear to process reduced forms differently, because non-natives produce more errors on reduced cognates than on non-cognates. While listening to reduced forms, non-natives appear to be hindered by the co-activated lexical representations of cognate forms in their native language.

Abstract

Statistical learning plays a key role in language processing, e.g., for speech segmentation. Older adults have been reported to show less statistical learning on the basis of visual input than younger adults. Given age-related changes in perception and cognition, we investigated whether statistical learning is also impaired in the auditory modality in older compared to younger adults and whether individual learning ability is associated with measures of perceptual (i.e., hearing sensitivity) and cognitive functioning in both age groups. Thirty younger and thirty older adults performed an auditory artificial-grammar-learning task to assess their statistical learning ability. In younger adults, perceptual effort came at the cost of processing resources required for learning. Inhibitory control (as indexed by Stroop colornaming performance) did not predict auditory learning. Overall, younger and older adults showed the same amount of auditory learning, indicating that statistical learning ability is preserved over the adult life span.

Abstract

This paper studies the influence of adverse listening conditions on exemplar effects in priming experiments that do not instruct participants to use their episodic memories. We conducted two lexical decision experiments, in which a prime and a target represented the same word type and could be spoken by the same or a different speaker. In Experiment 1, participants listened to clear speech, and showed no exemplar effects: they recognised repetitions by the same speaker as quickly as different speaker repetitions. In Experiment 2, the stimuli contained noise, and exemplar effects did arise. Importantly, Experiment 1 elicited longer average RTs than Experiment 2, a result that contradicts the time-course hypothesis, according to which exemplars only play a role when processing is slow. Instead, our findings support the hypothesis that exemplar effects arise under adverse listening conditions, when participants are stimulated to use their episodic memories in addition to their mental lexicons.

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

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

Abstract

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

Abstract

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

Abstract

Comprehension of pointing gestures is fundamental to human communication. However, the neural mechanisms
that subserve the integration of pointing gestures and speech in visual contexts in comprehension
are unclear. Here we present the results of an fMRI study in which participants watched images of an
actor pointing at an object while they listened to her referential speech. The use of a mismatch paradigm
revealed that the semantic unication of pointing gesture and speech in a triadic context recruits left
inferior frontal gyrus. Complementing previous ndings, this suggests that left inferior frontal gyrus
semantically integrates information across modalities and semiotic domains.

Abstract

From an early age, people exhibit strong links between certain visual (e.g. size) and acoustic (e.g. duration) dimensions. Do people instinctively extend these crossmodal correspondences to vocalization? We examine the ability of congenitally deaf Chinese children and young adults (age M = 12.4 years, SD = 3.7 years) to generate iconic vocalizations to distinguish items with contrasting magnitude (e.g., big vs. small ball). Both deaf and hearing (M = 10.1 years, SD = 0.83 years) participants produced longer, louder vocalizations for greater magnitude items. However, only hearing participants used pitch—higher pitch for greater magnitude – which counters the hypothesized, innate size “frequency code”, but fits with Mandarin language and culture. Thus our results show that the translation of visible magnitude into the duration and intensity of vocalization transcends auditory experience, whereas the use of pitch appears more malleable to linguistic and cultural influence.

Abstract

Scholars have documented substantial classes of iconic vocabulary in many non-Indo-European languages. In comparison, Indo-European languages like English are assumed to be arbitrary outside of a small number of onomatopoeic words. In three experiments, we asked English speakers to rate the iconicity of words from the MacArthur-Bates Communicative Developmental Inventory. We found English—contrary to common belief—exhibits iconicity that correlates with age of acquisition and differs across lexical classes. Words judged as most iconic are learned earlier, in accord with findings that iconic words are easier to learn. We also find that adjectives and verbs are more iconic than nouns, supporting the idea that iconicity provides an extra cue in learning more difficult abstract meanings. Our results provide new evidence for a relationship between iconicity and word learning and suggest iconicity may be a more pervasive property of spoken languages than previously thought.

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

We suggest that it is now possible to conduct research on a topic which might be called evolutionary geophonetics. The main question is how the climate influences the evolution of language. This involves biological adaptations to the climate that may affect biases in production and perception; cultural evolutionary adaptations of the sounds of a language to climatic conditions; and influences of the climate on language diversity and contact. We discuss these ideas with special reference to a recent hypothesis that lexical tone is not adaptive in dry climates (Everett, Blasi & Roberts, 2015).

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

This work focuses on efficient use of the training material by selecting the optimal set of model topologies. We do this by training multiple word models of each word class, based on a subclassification according to a priori knowledge of the training material. We will examine classification criteria with respect to duration of the word, gender of the speaker, position of the word in the utterance, pauses in the vicinity of the word, and combinations of these. Comparative experiments were carried out on a corpus consisting of Dutch spoken connected digit strings and isolated digits, which are recorded in a wide variety of acoustic conditions. The results show, that classification based on gender of the speaker, position of the digit in the string, pauses in the vicinity of the training tokens, and models based on a combination of these criteria perform significantly better than the set with single models per digit.

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

Processing of semantic information in language comprehension has been suggested to be modulated by attentional resources. Consequently, cognitive load would be expected to reduce semantic priming, but studies have yielded inconsistent results. This study investigated whether cognitive load affects semantic activation in speech processing in older adults, and whether this is modulated by individual differences in cognitive and hearing abilities. Older adults participated in an auditory continuous lexical decision task in a low-load and high-load condition. The group analysis showed only a marginally significant reduction of semantic priming in the high-load condition compared to the low-load condition. The individual differences analysis showed that semantic priming was significantly reduced under increased load in participants with poorer attention-switching control. Hence, a resource-demanding secondary task may affect the integration of spoken words into a coherent semantic representation for listeners with poorer attentional skills.

Abstract

Speakers can adapt their speech and co-speech gestures for
addressees. Here, we investigate whether this ability is
modulated by age. Younger and older adults participated in a
comic narration task in which one participant (the speaker)
narrated six short comic stories to another participant (the
addressee). One half of each story was known to both participants, the other half only to the speaker. Younger but
not older speakers used more words and gestures when narrating novel story content as opposed to known content.
We discuss cognitive and pragmatic explanations of these findings and relate them to theories of gesture production.

Abstract

Adaptation to altered auditory feedback has been shown to induce subsequent shifts in perception. However, it is uncertain whether these perceptual changes may generalize to other speech sounds. In this experiment, we tested whether exposing the production of a vowel to altered auditory feedback affects perceptual categorization of a consonant distinction. In two sessions, participants produced CVC words containing the vowel /i/, while intermittently categorizing stimuli drawn from a continuum between "see" and "she." In the first session feedback was unaltered, while in the second session the formants of the vowel were shifted 20% towards /u/. Adaptation to the altered vowel was found to reduce the proportion of perceived /S/ stimuli. We suggest that this reflects an alteration to the sensorimotor mapping that is shared between vowels and consonants.

Abstract

A corpus of digitized speech errors is used to compare the prosody of correction patterns for word-level vs. sound-level errors. Results for both peak F0 and perceived prosodic markedness confirm that speakers are more likely to mark corrections of word-level errors than corrections of sound-level errors, and that errors ambiguous between word-level and soundlevel (such as boat for moat) show correction patterns like those for sound level errors. This finding increases the plausibility of the claim that word-sound-ambiguous errors arise at the same level of processing as sound errors that do not form words.

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

Speakers adapt their speech and gestures in various ways for their audience. We investigated further whether they use
ostensive signals (eye gaze, ostensive speech (e.g. like this, this) or a combination of both) in relation to their gestures
when talking to different addressees, i.e., to another adult or a child in a multimodal demonstration task. While adults used
more eye gaze towards their gestures with other adults than with children, they were more likely to use combined
ostensive signals for children than for adults. Thus speakers mark the communicative relevance of their gestures with different types of ostensive signals and by taking different types of addressees into account.

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

Previous research [9] suggests that Dutch learners of (British) English are not able to express sarcasm prosodically in their L2. The present study investigates whether explicit training on the prosodic markers of sarcasm in English can improve learners’ realisation of sarcasm. Sarcastic speech was elicited in short simulated telephone conversations between Dutch advanced learners of English and a native British English-speaking ‘friend’ in two sessions, fourteen days apart. Between the two sessions, participants were trained by means of (1) a presentation, (2) directed independent practice, and (3) evaluation of participants’ production and individual feedback in small groups. L1 British English-speaking raters subsequently evaluated the degree of sarcastic sounding in the participants’ responses on a five-point scale. It was found that significantly higher sarcasm ratings were given to L2 learners’ production obtained after the training than that obtained before the training; explicit training on prosody has a positive effect on learners’ production of sarcasm.

Abstract

We report an individual with music-odor synaesthesia who experiences automatic and vivid odor sensations when she hears music. S’s odor associations were recorded on two days, and compared with those of two control participants. Overall, S produced longer descriptions, and her associations were of multiple odors at once, in comparison to controls who typically reported a single odor. Although odor associations were qualitatively different between S and controls, ratings of the consistency of their descriptions did not differ. This demonstrates that crossmodal associations between music and odor exist in non-synaesthetes too. We also found that S is better at discriminating between odors than control participants, and is more likely to experience emotion, memories and evaluations triggered by odors, demonstrating the broader impact of her synaesthesia.

Abstract

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

Abstract

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

Abstract

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

Abstract

Sequences of reaction times (RT) produced by participants in an experiment are not only influenced by the stimuli, but by many other factors as well, including fatigue, attention, experience, IQ, handedness, etc. These confounding factors result in longterm effects (such as a participant’s overall reaction capability) and in short- and medium-time fluctuations in RTs (often referred to as ‘local speed effects’). Because stimuli are usually presented in a random sequence different for each participant, local speed effects affect the underlying ‘true’ RTs of specific trials in different ways across participants. To be able to focus statistical analysis on the effects of the cognitive process under study, it is necessary to reduce the effect of confounding factors as much as possible. In this paper we propose and compare techniques and criteria for doing so, with focus on reducing (‘filtering’) the local speed effects. We show that filtering matters substantially for the significance analyses of predictors in linear mixed effect regression models. The performance of filtering is assessed by the average between-participant correlation between filtered RT sequences and by Akaike’s Information Criterion, an important measure of the goodness-of-fit of linear mixed effect regression models.

Abstract

This paper presents DIANA, a new computational model of human speech processing. It is the first model that simulates the complete processing chain from the on-line processing of an acoustic signal to the execution of a response, including reaction times. Moreover it assumes minimal modularity. DIANA consists of three components. The activation component computes a probabilistic match between the input acoustic signal and representations in DIANA’s lexicon, resulting in a list of word hypotheses changing over time as the input unfolds. The decision component operates on this list and selects a word as soon as sufficient evidence is available. Finally, the execution component accounts for the time to execute a behavioral action. We show that DIANA well simulates the average participant in a word recognition experiment.

Abstract

DIANA is an end-to-end computational model of speech processing, which takes as input the speech signal, and provides as output the orthographic transcription of the stimulus, a word/non-word judgment and the associated estimated reaction time. So far, the model has only been tested for Dutch. In this paper, we extend DIANA such that it can also process North American English. The model is tested by having it simulate human participants in a large scale North American English lexical decision experiment. The simulations show that DIANA can adequately approximate the reaction times of an average participant (r = 0.45). In addition, they indicate that DIANA does not yet adequately model the cognitive processes that take place after stimulus offset.

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

Apraxia of Speech (AOS) is a motor speech disorder whose precise nature is still poorly understood. A recent behavioural experiment featuring a noise masking paradigm suggests that AOS reflects a disruption of feedforward control, whereas feedback control is spared and plays a more prominent role in achieving and maintaining segmental contrasts [10]. In the present study, we set out to validate the interpretation of AOS as a feedforward impairment by means of a series of computational simulations with the DIVA model [6, 7] mimicking the behavioural experiment. Simulation results showed a larger reduction in vowel spacing and a smaller vowel dispersion in the masking condition compared to the no-masking condition for the simulated feedforward deficit, whereas the other groups showed an opposite pattern. These results mimic the patterns observed in the human data, corroborating the notion that AOS can be conceptualized as a deficit in feedforward control

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

This article describes how the tonal elements of two common Spanish intonation contours –the falling statement and the low-rising-falling request– align with the segmental string in broad-focus utterances differing in number of prosodic words. Using an imitation-and-completion task, we show that (i) the last stressed syllable of the utterance, traditionally viewed as carrying the ‘nuclear’ accent, associates with either a high or a low tonal element depending on phrase length (ii) that certain tonal elements can be realized or omitted depending on the availability of specific metrical positions in their intonational phrase, and (iii) that the high tonal element of the request contour associates with either a stressed syllable or an intonational phrase edge depending on phrase length. On the basis of these facts, and in contrast to previous descriptions of Spanish intonation relying on obligatory and constant nuclear contours (e.g., L* L% for all neutral statements), we argue for a less constrained intonational morphology involving tonal units linked to the segmental string via contour-specific principles.

Abstract

Violations of the maxims of Quantity occur when utterances provide more (over-specified) or less (under-specified) information than strictly required for referent identification. While behavioural datasuggest that under-specified expressions lead to comprehension difficulty and communicative failure, there is no consensus as to whether over-specified expressions are also detrimental to comprehension. In this study we shed light on this debate, providing neurophysiological evidence supporting the view that extra information facilitates comprehension. We further present novel evidence that referential failure due to under-specification is qualitatively different from explicit cases of referential failure, when no matching referential candidate is available in the context.

Abstract

In situated communication, reference to an entity in the shared visual context can be established using eitheranexpression that conveys precise (minimally specified) or redundant (over-specified) information. There is, however, along-lasting debate in psycholinguistics concerningwhether the latter hinders referential processing. We present evidence from an eyetrackingexperiment recordingfixations as well asthe Index of Cognitive Activity –a novel measure of cognitive workload –supporting the view that over-specifications facilitate processing. We further present originalevidence that, above and beyond the effect of specificity,referring expressions thatuniformly reduce referential entropyalso benefitprocessing

Abstract

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

Abstract

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

Abstract

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

Abstract

The task of automatic playlist continuation is generating a list of recommended tracks that can be added to an existing playlist. By suggesting appropriate tracks, i. e., songs to add to a playlist, a recommender system can increase the user engagement by making playlist creation easier, as well as extending listening beyond the end of current playlist. The ACM Recommender Systems Challenge 2018 focuses on such task. Spotify released a dataset of playlists, which includes a large number of playlists and associated track listings. Given a set of playlists from which a number of tracks have been withheld, the goal is predicting the missing tracks in those playlists. We participated in the challenge as the team Unconscious Bias and, in this paper, we present our approach. We extend adversarial autoencoders to the problem of automatic playlist continuation. We show how multiple input modalities, such as the playlist titles as well as track titles, artists and albums, can be incorporated in the playlist continuation task.

Abstract

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

Abstract

Languages combine arbitrary and iconic signals. How do iconic signals emerge and when do they persist? We present an experimental study of the role of iconicity in the emergence of structure in an artificial language. Using an iterated communication game in which we control the signalling medium as well as the meaning space, we study the evolution of communicative signals in transmission chains. This sheds light on how affordances of the communication medium shape and constrain the mappability and transmissibility of form-meaning pairs. We find that iconic signals can form the building blocks for wider compositional patterns