Publications

Displaying 101 - 129 of 129
  • Seidlmayer, E., Galke, L., Melnychuk, T., Schultz, C., Tochtermann, K., & Förstner, K. U. (2019). Take it personally - A Python library for data enrichment for infometrical applications. In M. Alam, R. Usbeck, T. Pellegrini, H. Sack, & Y. Sure-Vetter (Eds.), Proceedings of the Posters and Demo Track of the 15th International Conference on Semantic Systems co-located with 15th International Conference on Semantic Systems (SEMANTiCS 2019).

    Abstract

    Like every other social sphere, science is influenced by individual characteristics of researchers. However, for investigations on scientific networks, only little data about the social background of researchers, e.g. social origin, gender, affiliation etc., is available.
    This paper introduces ”Take it personally - TIP”, a conceptual model and library currently under development, which aims to support the
    semantic enrichment of publication databases with semantically related background information which resides elsewhere in the (semantic) web, such as Wikidata.
    The supplementary information enriches the original information in the publication databases and thus facilitates the creation of complex scientific knowledge graphs. Such enrichment helps to improve the scientometric analysis of scientific publications as they can also take social backgrounds of researchers into account and to understand social structure in research communities.
  • Seijdel, N., Sakmakidis, N., De Haan, E. H. F., Bohte, S. M., & Scholte, H. S. (2019). Implicit scene segmentation in deeper convolutional neural networks. In Proceedings of the 2019 Conference on Cognitive Computational Neuroscience (pp. 1059-1062). doi:10.32470/CCN.2019.1149-0.

    Abstract

    Feedforward deep convolutional neural networks (DCNNs) are matching and even surpassing human performance on object recognition. This performance suggests that activation of a loose collection of image
    features could support the recognition of natural object categories, without dedicated systems to solve specific visual subtasks. Recent findings in humans however, suggest that while feedforward activity may suffice for
    sparse scenes with isolated objects, additional visual operations ('routines') that aid the recognition process (e.g. segmentation or grouping) are needed for more complex scenes. Linking human visual processing to
    performance of DCNNs with increasing depth, we here explored if, how, and when object information is differentiated from the backgrounds they appear on. To this end, we controlled the information in both objects
    and backgrounds, as well as the relationship between them by adding noise, manipulating background congruence and systematically occluding parts of the image. Results indicated less distinction between object- and background features for more shallow networks. For those networks, we observed a benefit of training on segmented objects (as compared to unsegmented objects). Overall, deeper networks trained on natural
    (unsegmented) scenes seem to perform implicit 'segmentation' of the objects from their background, possibly by improved selection of relevant features.
  • Senft, G. (2000). COME and GO in Kilivila. In B. Palmer, & P. Geraghty (Eds.), SICOL. Proceedings of the second international conference on Oceanic linguistics: Volume 2, Historical and descriptive studies (pp. 105-136). Canberra: Pacific Linguistics.
  • Senft, G., & Smits, R. (Eds.). (2000). Max-Planck-Institute for Psycholinguistics: Annual report 2000. Nijmegen: MPI for Psycholinguistics.
  • Senft, G. (Ed.). (2000). Systems of nominal classification. Cambridge: Cambridge University Press.
  • Seuren, P. A. M. (2013). From Whorf to Montague: Explorations in the theory of language. Oxford: Oxford University Press.
  • Shayan, S., Moreira, A., Windhouwer, M., Koenig, A., & Drude, S. (2013). LEXUS 3 - a collaborative environment for multimedia lexica. In Proceedings of the Digital Humanities Conference 2013 (pp. 392-395).
  • Shen, C., & Janse, E. (2019). Articulatory control in speech production. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 2019) (pp. 2533-2537). Canberra, Australia: Australasian Speech Science and Technology Association Inc.
  • Shen, C., Cooke, M., & Janse, E. (2019). Individual articulatory control in speech enrichment. In M. Ochmann, M. Vorländer, & J. Fels (Eds.), Proceedings of the 23rd International Congress on Acoustics (pp. 5726-5730). Berlin: Deutsche Gesellschaft für Akustik.

    Abstract

    ndividual talkers may use various strategies to enrich their speech while speaking in noise (i.e., Lombard speech) to improve their intelligibility. The resulting acoustic-phonetic changes in Lombard speech vary amongst different speakers, but it is unclear what causes these talker differences, and what impact these differences have on intelligibility. This study investigates the potential role of articulatory control in talkers’ Lombard speech enrichment success. Seventy-eight speakers read out sentences in both their habitual style and in a condition where they were instructed to speak clearly while hearing loud speech-shaped noise. A diadochokinetic (DDK) speech task that requires speakers to repetitively produce word or non-word sequences as accurately and as rapidly as possible, was used to quantify their articulatory control. Individuals’ predicted intelligibility in both speaking styles (presented at -5 dB SNR) was measured using an acoustic glimpse-based metric: the High-Energy Glimpse Proportion (HEGP). Speakers’ HEGP scores show a clear effect of speaking condition (better HEGP scores in the Lombard than habitual condition), but no simple effect of articulatory control on HEGP, nor an interaction between speaking condition and articulatory control. This indicates that individuals’ speech enrichment success as measured by the HEGP metric was not predicted by DDK performance.
  • Smith, A. C., Monaghan, P., & Huettig, F. (2013). Modelling the effects of formal literacy training on language mediated visual attention. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci 2013) (pp. 3420-3425). Austin, TX: Cognitive Science Society.

    Abstract

    Recent empirical evidence suggests that language-mediated eye gaze is partly determined by level of formal literacy training. Huettig, Singh and Mishra (2011) showed that high-literate individuals' eye gaze was closely time locked to phonological overlap between a spoken target word and items presented in a visual display. In contrast, low-literate individuals' eye gaze was not related to phonological overlap, but was instead strongly influenced by semantic relationships between items. Our present study tests the hypothesis that this behavior is an emergent property of an increased ability to extract phonological structure from the speech signal, as in the case of high-literates, with low-literates more reliant on more coarse grained structure. This hypothesis was tested using a neural network model, that integrates linguistic information extracted from the speech signal with visual and semantic information within a central resource. We demonstrate that contrasts in fixation behavior similar to those observed between high and low literates emerge when models are trained on speech signals of contrasting granularity.
  • Spapé, M., Verdonschot, R. G., & Van Steenbergen, H. (2019). The E-Primer: An introduction to creating psychological experiments in E-Prime® (2nd ed. updated for E-Prime 3). Leiden: Leiden University Press.

    Abstract

    E-Prime® is the leading software suite by Psychology Software Tools for designing and running Psychology lab experiments. The E-Primer is the perfect accompanying guide: It provides all the necessary knowledge to make E-Prime accessible to everyone. You can learn the tools of Psychological science by following the E-Primer through a series of entertaining, step-by-step recipes that recreate classic experiments. The updated E-Primer expands its proven combination of simple explanations, interesting tutorials and fun exercises, and makes even the novice student quickly confident to create their dream experiment.
  • Speed, L. J., O'Meara, C., San Roque, L., & Majid, A. (Eds.). (2019). Perception Metaphors. Amsterdam: Benjamins.

    Abstract

    Metaphor allows us to think and talk about one thing in terms of another, ratcheting up our cognitive and expressive capacity. It gives us concrete terms for abstract phenomena, for example, ideas become things we can grasp or let go of. Perceptual experience—characterised as physical and relatively concrete—should be an ideal source domain in metaphor, and a less likely target. But is this the case across diverse languages? And are some sensory modalities perhaps more concrete than others? This volume presents critical new data on perception metaphors from over 40 languages, including many which are under-studied. Aside from the wealth of data from diverse languages—modern and historical; spoken and signed—a variety of methods (e.g., natural language corpora, experimental) and theoretical approaches are brought together. This collection highlights how perception metaphor can offer both a bedrock of common experience and a source of continuing innovation in human communication
  • Stivers, T., & Sidnell, J. (Eds.). (2013). The handbook on conversation analysis. Malden, MA: Wiley-Blackwell.

    Abstract

    Presenting a comprehensive, state-of-the-art overview of theoretical and descriptive research in the field, The Handbook of Conversation Analysis brings together contributions by leading international experts to provide an invaluable information resource and reference for scholars of social interaction across the areas of conversation analysis, discourse analysis, linguistic anthropology, interpersonal communication, discursive psychology and sociolinguistics. Ideal as an introduction to the field for upper level undergraduates and as an in-depth review of the latest developments for graduate level students and established scholars Five sections outline the history and theory, methods, fundamental concepts, and core contexts in the study of conversation, as well as topics central to conversation analysis Written by international conversation analysis experts, the book covers a wide range of topics and disciplines, from reviewing underlying structures of conversation, to describing conversation analysis' relationship to anthropology, communication, linguistics, psychology, and sociology
  • Sumner, M., Kurumada, C., Gafter, R., & Casillas, M. (2013). Phonetic variation and the recognition of words with pronunciation variants. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci 2013) (pp. 3486-3492). Austin, TX: Cognitive Science Society.
  • Ten Bosch, L., Mulder, K., & Boves, L. (2019). Phase synchronization between EEG signals as a function of differences between stimuli characteristics. In Proceedings of Interspeech 2019 (pp. 1213-1217). doi:10.21437/Interspeech.2019-2443.

    Abstract

    The neural processing of speech leads to specific patterns in the brain which can be measured as, e.g., EEG signals. When properly aligned with the speech input and averaged over many tokens, the Event Related Potential (ERP) signal is able to differentiate specific contrasts between speech signals. Well-known effects relate to the difference between expected and unexpected words, in particular in the N400, while effects in N100 and P200 are related to attention and acoustic onset effects. Most EEG studies deal with the amplitude of EEG signals over time, sidestepping the effect of phase and phase synchronization. This paper investigates the relation between phase in the EEG signals measured in an auditory lexical decision task by Dutch participants listening to full and reduced English word forms. We show that phase synchronization takes place across stimulus conditions, and that the so-called circular variance is narrowly related to the type of contrast between stimuli.
  • Ten Bosch, L., Boves, L., & Ernestus, M. (2013). Towards an end-to-end computational model of speech comprehension: simulating a lexical decision task. In Proceedings of INTERSPEECH 2013: 14th Annual Conference of the International Speech Communication Association (pp. 2822-2826).

    Abstract

    This paper describes a computational model of speech comprehension that takes the acoustic signal as input and predicts reaction times as observed in an auditory lexical decision task. By doing so, we explore a new generation of end-to-end computational models that are able to simulate the behaviour of human subjects participating in a psycholinguistic experiment. So far, nearly all computational models of speech comprehension do not start from the speech signal itself, but from abstract representations of the speech signal, while the few existing models that do start from the acoustic signal cannot directly model reaction times as obtained in comprehension experiments. The main functional components in our model are the perception stage, which is compatible with the psycholinguistic model Shortlist B and is implemented with techniques from automatic speech recognition, and the decision stage, which is based on the linear ballistic accumulation decision model. We successfully tested our model against data from 20 participants performing a largescale auditory lexical decision experiment. Analyses show that the model is a good predictor for the average judgment and reaction time for each word.
  • Ter Bekke, M., Ozyurek, A., & Ünal, E. (2019). Speaking but not gesturing predicts motion event memory within and across languages. In A. Goel, C. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 2940-2946). Montreal, QB: Cognitive Science Society.

    Abstract

    In everyday life, people see, describe and remember motion events. We tested whether the type of motion event information (path or manner) encoded in speech and gesture predicts which information is remembered and if this varies across speakers of typologically different languages. We focus on intransitive motion events (e.g., a woman running to a tree) that are described differently in speech and co-speech gesture across languages, based on how these languages typologically encode manner and path information (Kita & Özyürek, 2003; Talmy, 1985). Speakers of Dutch (n = 19) and Turkish (n = 22) watched and described motion events. With a surprise (i.e. unexpected) recognition memory task, memory for manner and path components of these events was measured. Neither Dutch nor Turkish speakers’ memory for manner went above chance levels. However, we found a positive relation between path speech and path change detection: participants who described the path during encoding were more accurate at detecting changes to the path of an event during the memory task. In addition, the relation between path speech and path memory changed with native language: for Dutch speakers encoding path in speech was related to improved path memory, but for Turkish speakers no such relation existed. For both languages, co-speech gesture did not predict memory speakers. We discuss the implications of these findings for our understanding of the relations between speech, gesture, type of encoding in language and memory.
  • Timmer, K., Ganushchak, L. Y., Mitlina, Y., & Schiller, N. O. (2013). Choosing first or second language phonology in 125 ms [Abstract]. Journal of Cognitive Neuroscience, 25 Suppl., 164.

    Abstract

    We are often in a bilingual situation (e.g., overhearing a conversation in the train). We investigated whether first (L1) and second language (L2) phonologies are automatically activated. A masked priming paradigm was used, with Russian words as targets and either Russian or English words as primes. Event-related potentials (ERPs) were recorded while Russian (L1) – English (L2) bilinguals read aloud L1 target words (e.g. РЕЙС /reis/ ‘fl ight’) primed with either L1 (e.g. РАНА /rana/ ‘wound’) or L2 words (e.g. PACK). Target words were read faster when they were preceded by phonologically related L1 primes but not by orthographically related L2 primes. ERPs showed orthographic priming in the 125-200 ms time window. Thus, both L1 and L2 phonologies are simultaneously activated during L1 reading. The results provide support for non-selective models of bilingual reading, which assume automatic activation of the non-target language phonology even when it is not required by the task.
  • Troncoso Ruiz, A., Ernestus, M., & Broersma, M. (2019). Learning to produce difficult L2 vowels: The effects of awareness-rasing, exposure and feedback. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 2019) (pp. 1094-1098). Canberra, Australia: Australasian Speech Science and Technology Association Inc.
  • Ünal, E., & Papafragou, A. (2013). Linguistic and conceptual representations of inference as a knowledge source. In S. Baiz, N. Goldman, & R. Hawkes (Eds.), Proceedings of the 37th Annual Boston University Conference on Language Development (BUCLD 37) (pp. 433-443). Boston: Cascadilla Press.
  • Van Dooren, A., Tulling, M., Cournane, A., & Hacquard, V. (2019). Discovering modal polysemy: Lexical aspect might help. In M. Brown, & B. Dailey (Eds.), BUCLD 43: Proceedings of the 43rd annual Boston University Conference on Language Development (pp. 203-216). Sommerville, MA: Cascadilla Press.
  • Van Valin Jr., R. D. (2000). Focus structure or abstract syntax? A role and reference grammar account of some ‘abstract’ syntactic phenomena. In Z. Estrada Fernández, & I. Barreras Aguilar (Eds.), Memorias del V Encuentro Internacional de Lingüística en el Noroeste: (2 v.) Estudios morfosintácticos (pp. 39-62). Hermosillo: Editorial Unison.
  • Van Putten, S. (2013). The meaning of the Avatime additive particle tsye. In M. Balbach, L. Benz, S. Genzel, M. Grubic, A. Renans, S. Schalowski, M. Stegenwallner, & A. Zeldes (Eds.), Information structure: Empirical perspectives on theory (pp. 55-74). Potsdam: Universitätsverlag Potsdam. Retrieved from http://nbn-resolving.de/urn/resolver.pl?urn=urn:nbn:de:kobv:517-opus-64804.
  • von Stutterheim, C., & Flecken, M. (Eds.). (2013). Principles of information organization in L2 discourse [Special Issue]. International Review of Applied linguistics in Language Teaching (IRAL), 51(2).
  • Wagner, M. A., Broersma, M., McQueen, J. M., & Lemhöfer, K. (2019). Imitating speech in an unfamiliar language and an unfamiliar non-native accent in the native language. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 1362-1366). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    This study concerns individual differences in speech imitation ability and the role that lexical representations play in imitation. We examined 1) whether imitation of sounds in an unfamiliar language (L0) is related to imitation of sounds in an unfamiliar
    non-native accent in the speaker’s native language (L1) and 2) whether it is easier or harder to imitate speech when you know the words to be imitated. Fifty-nine native Dutch speakers imitated words with target vowels in Basque (/a/ and /e/) and Greekaccented
    Dutch (/i/ and /u/). Spectral and durational
    analyses of the target vowels revealed no relationship between the success of L0 and L1 imitation and no difference in performance between tasks (i.e., L1
    imitation was neither aided nor blocked by lexical knowledge about the correct pronunciation). The results suggest instead that the relationship of the vowels to native phonological categories plays a bigger role in imitation
  • Weber, A. (2000). Phonotactic and acoustic cues for word segmentation in English. In Proceedings of the 6th International Conference on Spoken Language Processing (ICSLP 2000) (pp. 782-785).

    Abstract

    This study investigates the influence of both phonotactic and acoustic cues on the segmentation of spoken English. Listeners detected embedded English words in nonsense sequences (word spotting). Words aligned with phonotactic boundaries were easier to detect than words without such alignment. Acoustic cues to boundaries could also have signaled word boundaries, especially when word onsets lacked phonotactic alignment. However, only one of several durational boundary cues showed a marginally significant correlation with response times (RTs). The results suggest that word segmentation in English is influenced primarily by phonotactic constraints and only secondarily by acoustic aspects of the speech signal.
  • Weber, A. (2000). The role of phonotactics in the segmentation of native and non-native continuous speech. In A. Cutler, J. M. McQueen, & R. Zondervan (Eds.), Proceedings of SWAP, Workshop on Spoken Word Access Processes. Nijmegen: MPI for Psycholinguistics.

    Abstract

    Previous research has shown that listeners make use of their knowledge of phonotactic constraints to segment speech into individual words. The present study investigates the influence of phonotactics when segmenting a non-native language. German and English listeners detected embedded English words in nonsense sequences. German listeners also had knowledge of English, but English listeners had no knowledge of German. Word onsets were either aligned with a syllable boundary or not, according to the phonotactics of the two languages. Words aligned with either German or English phonotactic boundaries were easier for German listeners to detect than words without such alignment. Responses of English listeners were influenced primarily by English phonotactic alignment. The results suggest that both native and non-native phonotactic constraints influence lexical segmentation of a non-native, but familiar, language.
  • Wolf, M. C., Smith, A. C., Meyer, A. S., & Rowland, C. F. (2019). Modality effects in vocabulary acquisition. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 1212-1218). Montreal, QB: Cognitive Science Society.

    Abstract

    It is unknown whether modality affects the efficiency with which humans learn novel word forms and their meanings, with previous studies reporting both written and auditory advantages. The current study implements controls whose absence in previous work likely offers explanation for such contradictory findings. In two novel word learning experiments, participants were trained and tested on pseudoword - novel object pairs, with controls on: modality of test, modality of meaning, duration of exposure and transparency of word form. In both experiments word forms were presented in either their written or spoken form, each paired with a pictorial meaning (novel object). Following a 20-minute filler task, participants were tested on their ability to identify the picture-word form pairs on which they were trained. A between subjects design generated four participant groups per experiment 1) written training, written test; 2) written training, spoken test; 3) spoken training, written test; 4) spoken training, spoken test. In Experiment 1 the written stimulus was presented for a time period equal to the duration of the spoken form. Results showed that when the duration of exposure was equal, participants displayed a written training benefit. Given words can be read faster than the time taken for the spoken form to unfold, in Experiment 2 the written form was presented for 300 ms, sufficient time to read the word yet 65% shorter than the duration of the spoken form. No modality effect was observed under these conditions, when exposure to the word form was equivalent. These results demonstrate, at least for proficient readers, that when exposure to the word form is controlled across modalities the efficiency with which word form-meaning associations are learnt does not differ. Our results therefore suggest that, although we typically begin as aural-only word learners, we ultimately converge on developing learning mechanisms that learn equally efficiently from both written and spoken materials.
  • De Zubicaray, G. I., Acheson, D. J., & Hartsuiker, R. J. (Eds.). (2013). Mind what you say - general and specific mechanisms for monitoring in speech production [Research topic] [Special Issue]. Frontiers in Human Neuroscience. Retrieved from http://www.frontiersin.org/human_neuroscience/researchtopics/mind_what_you_say_-_general_an/1197.

    Abstract

    Psycholinguistic research has typically portrayed speech production as a relatively automatic process. This is because when errors are made, they occur as seldom as one in every thousand words we utter. However, it has long been recognised that we need some form of control over what we are currently saying and what we plan to say. This capacity to both monitor our inner speech and self-correct our speech output has often been assumed to be a property of the language comprehension system. More recently, it has been demonstrated that speech production benefits from interfacing with more general cognitive processes such as selective attention, short-term memory (STM) and online response monitoring to resolve potential conflict and successfully produce the output of a verbal plan. The conditions and levels of representation according to which these more general planning, monitoring and control processes are engaged during speech production remain poorly understood. Moreover, there remains a paucity of information about their neural substrates, despite some of the first evidence of more general monitoring having come from electrophysiological studies of error related negativities (ERNs). While aphasic speech errors continue to be a rich source of information, there has been comparatively little research focus on instances of speech repair. The purpose of this Frontiers Research Topic is to provide a forum for researchers to contribute investigations employing behavioural, neuropsychological, electrophysiological, neuroimaging and virtual lesioning techniques. In addition, while the focus of the research topic is on novel findings, we welcome submission of computational simulations, review articles and methods papers.

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