Publications

Abstract

This study investigates the effects of adult age and speaker abilities on articulatory precision for sibilant productions. Normal-hearing young adults with
better sibilant discrimination have been shown to produce greater spectral sibilant contrasts. As reduced auditory feedback may gradually impact on feedforward
commands, we investigate whether articulatory precision as indexed by spectral mean for [s] and [S] decreases with age, and more particularly with agerelated
hearing loss. Younger, middle-aged and older adults read aloud words starting with the sibilants [s] or [S]. Possible effects of cognitive, perceptual, linguistic and sociolinguistic background variables
on the sibilants’ acoustics were also investigated. Sibilant contrasts were less pronounced for male than female speakers. Most importantly, for the fricative
[s], the spectral mean was modulated by individual high-frequency hearing loss, but not age. These results underscore that even mild hearing loss already affects articulatory precision.

Abstract

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

Abstract

This paper examines the language-specific aspect of the TIME PASSING IS MOTION metaphor and suggests that the temporal construal of time can be influenced by a person's second language. Ahrens and Huang (2002) have analyzed the source domain of MOTION for the TIME metaphor into two special cases. In the special case one, TIME PASSING is an object that moves towards an ego. For example, qimuokao kuai dao le "the final exam is approaching." In the special case two, TIME PASSING is a point (that a plural ego is attached to) that moves across a landscape. For example, women kuai dao qimuokao le "we are approaching the final exam." In addition, in English, the ego in the special case one faces the future while in Chinese, the ego faces the past. The current experiment hypothesizes that English influences the choice of the orientation of the ego in native Chinese speakers who speak English as the second language. 54 subjects are asked to switch the clock time one hour forward. Results show that native Chinese speakers living in the Chinese speaking country tend to move the clock one hour forward to the past (92%) while native Chinese speakers living in an English speaking country are less likely to do so (60%). This implies that the experience of English influences the conceptualization of time in Mandarin Chinese.

Abstract

Speakers of English habitually encode motion events using manner-of-motion verbs (e.g., spin, roll, slide) whereas Spanish speakers rely on path-of-motion verbs (e.g., enter, exit, approach). Here, we ask whether the language-specific verb representations used in encoding motion events induce different modes of “thinking-for-speaking” in Spanish–English bilinguals. That is, assuming that the verb encodes the most salient information in the clause, do bilinguals find the path of motion to be more salient than manner of motion if they had previously described the motion event using Spanish versus English? In our study, Spanish–English bilinguals described a set of target motion events in either English or Spanish and then participated in a nonlinguistic similarity judgment task in which they viewed the target motion events individually (e.g., a ball rolling into a cave) followed by two variants a “same-path” variant such as a ball sliding into a cave or a “same-manner” variant such as a ball rolling away from a cave). Participants had to select one of the two variants that they judged to be more similar to the target event: The event that shared the same path of motion as the target versus the one that shared the same manner of motion. Our findings show that bilingual speakers were more likely to classify two motion events as being similar if they shared the same path of motion and if they had previously described the target motion events in Spanish versus in English. Our study provides further evidence for the “thinking-for-speaking” hypothesis by demonstrating that bilingual speakers can flexibly shift between language-specific construals of the same event “on-the-fly.”

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

The topic of this paper is the way in which speakers order information in discourse. I will refer to this issue with the term "linearization", and will begin with two types of general remarks. The first one concerns the scope and relevance of the problem with reference to some existing literature. The second set of general remarks will be about the place of linearization in a theory of the speaker. The following, and main part of this paper, will be a summary report of research of linearization in a limited, but well-defined domain of discourse, namely the description of spatial networks.

Abstract

This questionnaire is designed to explore how spatial relations are encoded in Australian language, but may be of interest to researchers further afield.

Abstract

This questionnaire is designed to explore how spatial relations are encoded in Australian language, but may be of interest to researchers further afield.

Abstract

These classic tasks can be used to explore spatial reference in field settings. They provide a language-independent metric for eliciting spatial language, using a “director-matcher” paradigm. The Man and Tree task deals with location on the horizontal plane with both featured (man) and non-featured (e.g., tree) objects. The Space Games depict various objects (e.g. bananas, lemons) and elicit spatial contrasts not obviously lexicalisable in English.

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

The lexicon is central to the concerns of disparate disciplines and has correspondingly elicited conflicting proposals about some of its foundational properties. Some suppose that word meanings and their associated concepts are largely universal, while others note that local cultural interests infiltrate every category in the lexicon. This chapter reviews research in two semantic domains—perception and the body—in order to illustrate crosslinguistic similarities and differences in semantic fields. Data is considered from a wide array of languages, especially those from small-scale indigenous communities which are often overlooked. In every lexical field we find considerable variation across cultures, raising the question of where this variation comes from. Is it the result of different ecological or environmental niches, cultural practices, or accidents of historical pasts? Current evidence suggests that diverse pressures differentially shape lexical fields.

Abstract

What is the relationship between the language we speak and the way we think? Researchers working at the interface of language and cognition hope to understand the complex interplay between linguistic structures and the way the mind works. This is thorny territory in anthropology and its closely allied disciplines, such as linguistics and psychology.

Abstract

Concepts are so fundamental to human cognition that Fodor declared the heart of a cognitive science to be its theory of concepts. To study concepts, though, cognitive scientists need to be able to identify some. The prevailing assumption has been that they are revealed by words such as triangle, table, and robin. But languages vary dramatically in how they carve up the world with names. Either ordinary concepts must be heavily language dependent, or names cannot be a direct route to concepts. We asked speakers of English, Dutch, Spanish, and Japanese to name a set of 36 video clips of human locomotion and to judge the similarities among them. We investigated what name inventories, name extensions, scaling solutions on name similarity, and scaling solutions on nonlinguistic similarity from the groups, individually and together, suggest about the underlying concepts. Aggregated naming data and similarity solutions converged on results distinct from individual languages.

Abstract

Words are fundamental to reading and yet over a century of research has not masked the controversies around how words are recognized. We review some old and new research that disproves simple ideas such as words are read as wholes or are simply mapped directly to spoken language. We also review theory and research relevant to the question of sublexical influences in word recognition. We describe orthography and phonology, how they are related to each other and describe a series of new experiments on how these sources of information are processed. Tasks include lexical decision, perceptual identification, and naming. Dependent measures are reaction time, accuracy of performance, and a new measure, initial phoneme duration, that refers to the duration of the first phoneme when the target word is pronounced. Important factors in resolving the controversies include the realization that reading has multiple determinants, as well as evaluating the type of task, proper controls such as familiarity of the test items and accuracy of measurement of the response. We also address potential limitations with measures related to the mapping between orthography and phonology, and show that the existence of a sound-to-spelling consistency effect does not require interactive activation, but can be explained and predicted by a feedforward model, the Fuzzy logical model of perception.

Abstract

Information structure is a subfield of linguistic research dealing with the ways speakers encode instructions to the hearer on how to process the message relative to their temporary mental states. To this end, sentences are segmented into parts conveying known and yet-unknown information, usually labeled ‘topic’ and ‘focus.’ Many languages have developed specialized grammatical and lexical means of indicating this segmentation.

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 lexical statistics on the pattern of occurrence of words embedded in other words. We report the results of an analysis of 25000 words, varying in length from two to six syllables, extracted from a phonetically-coded English dictionary (The Longman Dictionary of Contemporary English). Each syllable, and each string of syllables within each word was checked against the dictionary. Two analyses are presented: the first used a complete list of polysyllables, with look-up on the entire dictionary; the second used a sublist of content words, counting only embedded words which were themselves content words. The results have important implications for models of human speech recognition. The efficiency of these models depends, in different ways, on the number and location of words within words.

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

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

An inference is defined as the information that is not expressed explicitly by the text but is derived on the basis of the understander's knowledge and is encoded in the mental representation of the text. Inferencing is considered as a central component in discourse understanding. Experimental methods to detect inferences, established findings, and some developments are reviewed. Attention is paid to the relation between inference processes and the brain.

Abstract

Egophoric verbal marking is a typological feature common to Barbacoan languages, but otherwise unknown in the Andean sphere. The verbal systems of three out of the four living Barbacoan languages, Cha’palaa, Tsafiki and Awa Pit, have previously been shown to express egophoric contrasts. The status of Guambiano has, however, remained uncertain. In this chapter, I show that there are in fact two layers of egophoric or egophoric-like marking visible in Guambiano’s grammar. Guambiano patterns with certain other (non-Barbacoan) languages in having ego-categories which function within a broader evidential system. It is additionally possible to detect what is possibly a more archaic layer of egophoric marking in Guambiano’s verbal system. This marking may be inherited from a common Barbacoan system, thus pointing to a potential genealogical basis for the egophoric patterning common to these languages. The multiple formal expressions of egophoricity apparent both within and across the four languages reveal how egophoric contrasts are susceptible to structural renewal, suggesting a pan-Barbacoan preoccupation with the linguistic encoding of self-knowledge.

Abstract

To what extent are the planning processes involved in producing sentences fine-tuned to grammatical properties of specific languages? In this chapter we survey the small body of cross-linguistic research that bears on this question, focusing in particular on recent evidence from eye-tracking studies. Because eye-tracking methods provide a very fine-grained temporal measure of how conceptual and linguistic planning unfold in real time, they serve as an important complement to standard psycholinguistic methods. Moreover, the advent of portable eye-trackers in recent years has, for the first time, allowed eye-tracking techniques to be used with language populations that are located far away from university laboratories. This has created the exciting opportunity to extend the typological base of vision-based psycholinguistic research and address key questions in language production with new language comparisons.

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

We report two experiments in which vowels and steady-state consonants served as targets in a speeded detection task. In the first experiment, two vowels were compared with one voiced and once unvoiced fricative. Response times (RTs) to the vowels were longer than to the fricatives. The error rate was higher for the consonants. Consonants in word-final position produced the shortest RTs, For the vowels, RT correlated negatively with target duration. In the second experiment, the same two vowel targets were compared with two nasals. This time there was no significant difference in RTs, but the error rate was still significantly higher for the consonants. Error rate and length correlated negatively for the vowels only. We conclude that RT differences between phonemes are independent of vocalic or consonantal status. Instead, we argue that the process of phoneme detection reflects more finely grained differences in acoustic/articulatory structure within the phonemic repertoire.

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

Our ability to use language is multimodal and requires tight coordination between what is expressed in speech and in gesture, such as pointing or iconic gestures that convey semantic, syntactic and pragmatic information related to speakers’ messages. Interestingly, what is expressed in gesture and how it is coordinated with speech differs in speakers of different languages. This paper discusses recent findings on the development of children’s multimodal expressions taking cross-linguistic variation into account. Although some aspects of speech-gesture development show language-specificity from an early age, it might still take children until nine years of age to exhibit fully adult patterns of cross-linguistic variation. These findings reveal insights about how children coordinate different levels of representations given that their development is constrained by patterns that are specific to their languages.