Publications

Displaying 1 - 100 of 134
  • Alhama, R. G., Siegelman, N., Frost, R., & Armstrong, B. C. (2019). The role of information in visual word recognition: A perceptually-constrained connectionist account. In A. Goel, C. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 83-89). Austin, TX: Cognitive Science Society.

    Abstract

    Proficient readers typically fixate near the center of a word, with a slight bias towards word onset. We explore a novel account of this phenomenon based on combining information-theory with visual perceptual constraints in a connectionist model of visual word recognition. This account posits that the amount of information-content available for word identification varies across fixation locations and across languages, thereby explaining the overall fixation location bias in different languages, making the novel prediction that certain words are more readily identified when fixating at an atypical fixation location, and predicting specific cross-linguistic differences. We tested these predictions across several simulations in English and Hebrew, and in a pilot behavioral experiment. Results confirmed that the bias to fixate closer to word onset aligns with maximizing information in the visual signal, that some words are more readily identified at atypical fixation locations, and that these effects vary to some degree across languages.
  • Anastasopoulos, A., Lekakou, M., Quer, J., Zimianiti, E., DeBenedetto, J., & Chiang, D. (2018). Part-of-speech tagging on an endangered language: a parallel Griko-Italian Resource. In Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018) (pp. 2529-2539).

    Abstract

    Most work on part-of-speech (POS) tagging is focused on high resource languages, or examines low-resource and active learning settings through simulated studies. We evaluate POS tagging techniques on an actual endangered language, Griko. We present a resource that contains 114 narratives in Griko, along with sentence-level translations in Italian, and provides gold annotations for the test set. Based on a previously collected small corpus, we investigate several traditional methods, as well as methods that take advantage of monolingual data or project cross-lingual POS tags. We show that the combination of a semi-supervised method with cross-lingual transfer is more appropriate for this extremely challenging setting, with the best tagger achieving an accuracy of 72.9%. With an applied active learning scheme, which we use to collect sentence-level annotations over the test set, we achieve improvements of more than 21 percentage points
  • Badimala, P., Mishra, C., Venkataramana, R. K. M., Bukhari, S. S., & Dengel, A. (2019). A Study of Various Text Augmentation Techniques for Relation Classification in Free Text. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods (pp. 360-367). Setúbal, Portugal: SciTePress Digital Library. doi:10.5220/0007311003600367.

    Abstract

    Data augmentation techniques have been widely used in visual recognition tasks as it is easy to generate new
    data by simple and straight forward image transformations. However, when it comes to text data augmen-
    tations, it is difficult to find appropriate transformation techniques which also preserve the contextual and
    grammatical structure of language texts. In this paper, we explore various text data augmentation techniques
    in text space and word embedding space. We study the effect of various augmented datasets on the efficiency
    of different deep learning models for relation classification in text.
  • Basnakova, J. (2019). Beyond the language given: The neurobiological infrastructure for pragmatic inferencing. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Bauer, B. L. M. (1999). Aspects of impersonal constructions in Late Latin. In H. Petersmann, & R. Kettelmann (Eds.), Latin vulgaire – latin tardif V (pp. 209-211). Heidelberg: Winter.
  • Bentum, M., Ten Bosch, L., Van den Bosch, A., & Ernestus, M. (2019). Listening with great expectations: An investigation of word form anticipations in naturalistic speech. In Proceedings of Interspeech 2019 (pp. 2265-2269). doi:10.21437/Interspeech.2019-2741.

    Abstract

    The event-related potential (ERP) component named phonological mismatch negativity (PMN) arises when listeners hear an unexpected word form in a spoken sentence [1]. The PMN is thought to reflect the mismatch between expected and perceived auditory speech input. In this paper, we use the PMN to test a central premise in the predictive coding framework [2], namely that the mismatch between prior expectations and sensory input is an important mechanism of perception. We test this with natural speech materials containing approximately 50,000 word tokens. The corresponding EEG-signal was recorded while participants (n = 48) listened to these materials. Following [3], we quantify the mismatch with two word probability distributions (WPD): a WPD based on preceding context, and a WPD that is additionally updated based on the incoming audio of the current word. We use the between-WPD cross entropy for each word in the utterances and show that a higher cross entropy correlates with a more negative PMN. Our results show that listeners anticipate auditory input while processing each word in naturalistic speech. Moreover, complementing previous research, we show that predictive language processing occurs across the whole probability spectrum.
  • Bentum, M., Ten Bosch, L., Van den Bosch, A., & Ernestus, M. (2019). Quantifying expectation modulation in human speech processing. In Proceedings of Interspeech 2019 (pp. 2270-2274). doi:10.21437/Interspeech.2019-2685.

    Abstract

    The mismatch between top-down predicted and bottom-up perceptual input is an important mechanism of perception according to the predictive coding framework (Friston, [1]). In this paper we develop and validate a new information-theoretic measure that quantifies the mismatch between expected and observed auditory input during speech processing. We argue that such a mismatch measure is useful for the study of speech processing. To compute the mismatch measure, we use naturalistic speech materials containing approximately 50,000 word tokens. For each word token we first estimate the prior word probability distribution with the aid of statistical language modelling, and next use automatic speech recognition to update this word probability distribution based on the unfolding speech signal. We validate the mismatch measure with multiple analyses, and show that the auditory-based update improves the probability of the correct word and lowers the uncertainty of the word probability distribution. Based on these results, we argue that it is possible to explicitly estimate the mismatch between predicted and perceived speech input with the cross entropy between word expectations computed before and after an auditory update.
  • Bentz, C., Dediu, D., Verkerk, A., & Jäger, G. (2018). Language family trees reflect geography and demography beyond neutral drift. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 38-40). Toruń, Poland: NCU Press. doi:10.12775/3991-1.006.
  • Brand, J., Monaghan, P., & Walker, P. (2018). Changing Signs: Testing How Sound-Symbolism Supports Early Word Learning. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1398-1403). Austin, TX: Cognitive Science Society.

    Abstract

    Learning a language involves learning how to map specific forms onto their associated meanings. Such mappings can utilise arbitrariness and non-arbitrariness, yet, our understanding of how these two systems operate at different stages of vocabulary development is still not fully understood. The Sound-Symbolism Bootstrapping Hypothesis (SSBH) proposes that sound-symbolism is essential for word learning to commence, but empirical evidence of exactly how sound-symbolism influences language learning is still sparse. It may be the case that sound-symbolism supports acquisition of categories of meaning, or that it enables acquisition of individualized word meanings. In two Experiments where participants learned form-meaning mappings from either sound-symbolic or arbitrary languages, we demonstrate the changing roles of sound-symbolism and arbitrariness for different vocabulary sizes, showing that sound-symbolism provides an advantage for learning of broad categories, which may then transfer to support learning individual words, whereas an arbitrary language impedes acquisition of categories of sound to meaning.
  • Brehm, L., Jackson, C. N., & Miller, K. L. (2019). Incremental interpretation in the first and second language. In M. Brown, & B. Dailey (Eds.), BUCLD 43: Proceedings of the 43rd annual Boston University Conference on Language Development (pp. 109-122). Sommerville, MA: Cascadilla Press.
  • Bruggeman, L., & Cutler, A. (2019). The dynamics of lexical activation and competition in bilinguals’ first versus second language. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 1342-1346). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    Speech input causes listeners to activate multiple
    candidate words which then compete with one
    another. These include onset competitors, that share a
    beginning (bumper, butter), but also, counterintuitively,
    rhyme competitors, sharing an ending
    (bumper, jumper). In L1, competition is typically
    stronger for onset than for rhyme. In L2, onset
    competition has been attested but rhyme competition
    has heretofore remained largely unexamined. We
    assessed L1 (Dutch) and L2 (English) word
    recognition by the same late-bilingual individuals. In
    each language, eye gaze was recorded as listeners
    heard sentences and viewed sets of drawings: three
    unrelated, one depicting an onset or rhyme competitor
    of a word in the input. Activation patterns revealed
    substantial onset competition but no significant
    rhyme competition in either L1 or L2. Rhyme
    competition may thus be a “luxury” feature of
    maximally efficient listening, to be abandoned when
    resources are scarcer, as in listening by late
    bilinguals, in either language.
  • Byun, K.-S., De Vos, C., Roberts, S. G., & Levinson, S. C. (2018). Interactive sequences modulate the selection of expressive forms in cross-signing. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 67-69). Toruń, Poland: NCU Press. doi:10.12775/3991-1.012.
  • Corps, R. E. (2018). Coordinating utterances during conversational dialogue: The role of content and timing predictions. PhD Thesis, The University of Edinburgh, Edinburgh.
  • Cristia, A., Ganesh, S., Casillas, M., & Ganapathy, S. (2018). Talker diarization in the wild: The case of child-centered daylong audio-recordings. In Proceedings of Interspeech 2018 (pp. 2583-2587). doi:10.21437/Interspeech.2018-2078.

    Abstract

    Speaker diarization (answering 'who spoke when') is a widely researched subject within speech technology. Numerous experiments have been run on datasets built from broadcast news, meeting data, and call centers—the task sometimes appears close to being solved. Much less work has begun to tackle the hardest diarization task of all: spontaneous conversations in real-world settings. Such diarization would be particularly useful for studies of language acquisition, where researchers investigate the speech children produce and hear in their daily lives. In this paper, we study audio gathered with a recorder worn by small children as they went about their normal days. As a result, each child was exposed to different acoustic environments with a multitude of background noises and a varying number of adults and peers. The inconsistency of speech and noise within and across samples poses a challenging task for speaker diarization systems, which we tackled via retraining and data augmentation techniques. We further studied sources of structured variation across raw audio files, including the impact of speaker type distribution, proportion of speech from children, and child age on diarization performance. We discuss the extent to which these findings might generalize to other samples of speech in the wild.
  • Croijmans, I. (2018). Wine expertise shapes olfactory language and cognition. PhD Thesis, Radboud University, Nijmegen.
  • Cutler, A., Burchfield, A., & Antoniou, M. (2019). A criterial interlocutor tally for successful talker adaptation? In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 1485-1489). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    Part of the remarkable efficiency of listening is
    accommodation to unfamiliar talkers’ specific
    pronunciations by retuning of phonemic intercategory
    boundaries. Such retuning occurs in second
    (L2) as well as first language (L1); however, recent
    research with emigrés revealed successful adaptation
    in the environmental L2 but, unprecedentedly, not in
    L1 despite continuing L1 use. A possible explanation
    involving relative exposure to novel talkers is here
    tested in heritage language users with Mandarin as
    family L1 and English as environmental language. In
    English, exposure to an ambiguous sound in
    disambiguating word contexts prompted the expected
    adjustment of phonemic boundaries in subsequent
    categorisation. However, no adjustment occurred in
    Mandarin, again despite regular use. Participants
    reported highly asymmetric interlocutor counts in the
    two languages. We conclude that successful retuning
    ability requires regular exposure to novel talkers in
    the language in question, a criterion not met for the
    emigrés’ or for these heritage users’ L1.
  • Ip, M. H. K., & Cutler, A. (2018). Asymmetric efficiency of juncture perception in L1 and L2. In K. Klessa, J. Bachan, A. Wagner, M. Karpiński, & D. Śledziński (Eds.), Proceedings of Speech Prosody 2018 (pp. 289-296). Baixas, France: ISCA. doi:10.21437/SpeechProsody.2018-59.

    Abstract

    In two experiments, Mandarin listeners resolved potential syntactic ambiguities in spoken utterances in (a) their native language (L1) and (b) English which they had learned as a second language (L2). A new disambiguation task was used, requiring speeded responses to select the correct meaning for structurally ambiguous sentences. Importantly, the ambiguities used in the study are identical in Mandarin and in English, and production data show that prosodic disambiguation of this type of ambiguity is also realised very similarly in the two languages. The perceptual results here showed however that listeners’ response patterns differed for L1 and L2, although there was a significant increase in similarity between the two response patterns with increasing exposure to the L2. Thus identical ambiguity and comparable disambiguation patterns in L1 and L2 do not lead to immediate application of the appropriate L1 listening strategy to L2; instead, it appears that such a strategy may have to be learned anew for the L2.
  • Ip, M. H. K., & Cutler, A. (2018). Cue equivalence in prosodic entrainment for focus detection. In J. Epps, J. Wolfe, J. Smith, & C. Jones (Eds.), Proceedings of the 17th Australasian International Conference on Speech Science and Technology (pp. 153-156).

    Abstract

    Using a phoneme detection task, the present series of
    experiments examines whether listeners can entrain to
    different combinations of prosodic cues to predict where focus
    will fall in an utterance. The stimuli were recorded by four
    female native speakers of Australian English who happened to
    have used different prosodic cues to produce sentences with
    prosodic focus: a combination of duration cues, mean and
    maximum F0, F0 range, and longer pre-target interval before
    the focused word onset, only mean F0 cues, only pre-target
    interval, and only duration cues. Results revealed that listeners
    can entrain in almost every condition except for where
    duration was the only reliable cue. Our findings suggest that
    listeners are flexible in the cues they use for focus processing.
  • Cutler, A., Burchfield, L. A., & Antoniou, M. (2018). Factors affecting talker adaptation in a second language. In J. Epps, J. Wolfe, J. Smith, & C. Jones (Eds.), Proceedings of the 17th Australasian International Conference on Speech Science and Technology (pp. 33-36).

    Abstract

    Listeners adapt rapidly to previously unheard talkers by
    adjusting phoneme categories using lexical knowledge, in a
    process termed lexically-guided perceptual learning. Although
    this is firmly established for listening in the native language
    (L1), perceptual flexibility in second languages (L2) is as yet
    less well understood. We report two experiments examining L1
    and L2 perceptual learning, the first in Mandarin-English late
    bilinguals, the second in Australian learners of Mandarin. Both
    studies showed stronger learning in L1; in L2, however,
    learning appeared for the English-L1 group but not for the
    Mandarin-L1 group. Phonological mapping differences from
    the L1 to the L2 are suggested as the reason for this result.
  • Cutler, A., Van Ooijen, B., & Norris, D. (1999). Vowels, consonants, and lexical activation. In J. Ohala, Y. Hasegawa, M. Ohala, D. Granville, & A. Bailey (Eds.), Proceedings of the Fourteenth International Congress of Phonetic Sciences: Vol. 3 (pp. 2053-2056). Berkeley: University of California.

    Abstract

    Two lexical decision studies examined the effects of single-phoneme mismatches on lexical activation in spoken-word recognition. One study was carried out in English, and involved spoken primes and visually presented lexical decision targets. The other study was carried out in Dutch, and primes and targets were both presented auditorily. Facilitation was found only for spoken targets preceded immediately by spoken primes; no facilitation occurred when targets were presented visually, or when intervening input occurred between prime and target. The effects of vowel mismatches and consonant mismatches were equivalent.
  • Delgado, T., Ravignani, A., Verhoef, T., Thompson, B., Grossi, T., & Kirby, S. (2018). Cultural transmission of melodic and rhythmic universals: Four experiments and a model. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 89-91). Toruń, Poland: NCU Press. doi:10.12775/3991-1.019.
  • Dideriksen, C., Fusaroli, R., Tylén, K., Dingemanse, M., & Christiansen, M. H. (2019). Contextualizing Conversational Strategies: Backchannel, Repair and Linguistic Alignment in Spontaneous and Task-Oriented Conversations. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society (CogSci 2019) (pp. 261-267). Montreal, QB: Cognitive Science Society.

    Abstract

    Do interlocutors adjust their conversational strategies to the specific contextual demands of a given situation? Prior studies have yielded conflicting results, making it unclear how strategies vary with demands. We combine insights from qualitative and quantitative approaches in a within-participant experimental design involving two different contexts: spontaneously occurring conversations (SOC) and task-oriented conversations (TOC). We systematically assess backchanneling, other-repair and linguistic alignment. We find that SOC exhibit a higher number of backchannels, a reduced and more generic repair format and higher rates of lexical and syntactic alignment. TOC are characterized by a high number of specific repairs and a lower rate of lexical and syntactic alignment. However, when alignment occurs, more linguistic forms are aligned. The findings show that conversational strategies adapt to specific contextual demands.
  • Dieuleveut, A., Van Dooren, A., Cournane, A., & Hacquard, V. (2019). Acquiring the force of modals: Sig you guess what sig means? In M. Brown, & B. Dailey (Eds.), BUCLD 43: Proceedings of the 43rd annual Boston University Conference on Language Development (pp. 189-202). Sommerville, MA: Cascadilla Press.
  • Drijvers, L. (2019). On the oscillatory dynamics underlying speech-gesture integration in clear and adverse listening conditions. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Drozdova, P. (2018). The effects of nativeness and background noise on the perceptual learning of voices and ambiguous sounds. PhD Thesis, Radboud University, Nijmegen.
  • Duarte, R., Uhlmann, M., Van den Broek, D., Fitz, H., Petersson, K. M., & Morrison, A. (2018). Encoding symbolic sequences with spiking neural reservoirs. In Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN). doi:10.1109/IJCNN.2018.8489114.

    Abstract

    Biologically inspired spiking networks are an important tool to study the nature of computation and cognition in neural systems. In this work, we investigate the representational capacity of spiking networks engaged in an identity mapping task. We compare two schemes for encoding symbolic input, one in which input is injected as a direct current and one where input is delivered as a spatio-temporal spike pattern. We test the ability of networks to discriminate their input as a function of the number of distinct input symbols. We also compare performance using either membrane potentials or filtered spike trains as state variable. Furthermore, we investigate how the circuit behavior depends on the balance between excitation and inhibition, and the degree of synchrony and regularity in its internal dynamics. Finally, we compare different linear methods of decoding population activity onto desired target labels. Overall, our results suggest that even this simple mapping task is strongly influenced by design choices on input encoding, state-variables, circuit characteristics and decoding methods, and these factors can interact in complex ways. This work highlights the importance of constraining computational network models of behavior by available neurobiological evidence.
  • Eijk, L., Ernestus, M., & Schriefers, H. (2019). Alignment of pitch and articulation rate. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 2690-2694). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    Previous studies have shown that speakers align their speech to each other at multiple linguistic levels. This study investigates whether alignment is mostly the result of priming from the immediately preceding
    speech materials, focussing on pitch and articulation rate (AR). Native Dutch speakers completed sentences, first by themselves (pre-test), then in alternation with Confederate 1 (Round 1), with Confederate 2 (Round 2), with Confederate 1 again
    (Round 3), and lastly by themselves again (post-test). Results indicate that participants aligned to the confederates and that this alignment lasted during the post-test. The confederates’ directly preceding sentences were not good predictors for the participants’ pitch and AR. Overall, the results indicate that alignment is more of a global effect than a local priming effect.
  • Ergin, R., Senghas, A., Jackendoff, R., & Gleitman, L. (2018). Structural cues for symmetry, asymmetry, and non-symmetry in Central Taurus Sign Language. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 104-106). Toruń, Poland: NCU Press. doi:10.12775/3991-1.025.
  • Essegbey, J. (1999). Inherent complement verbs revisited: Towards an understanding of argument structure in Ewe. PhD Thesis, Radboud University Nijmegen, Nijmegen. doi:10.17617/2.2057668.
  • Estruch, S. B. (2018). Characterization of transcription factors in monogenic disorders of speech and language. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Fairs, A. (2019). Linguistic dual-tasking: Understanding temporal overlap between production and comprehension. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Felker, E. R., Ernestus, M., & Broersma, M. (2019). Evaluating dictation task measures for the study of speech perception. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 2019) (pp. 383-387). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    This paper shows that the dictation task, a well-
    known testing instrument in language education, has
    untapped potential as a research tool for studying
    speech perception. We describe how transcriptions
    can be scored on measures of lexical, orthographic,
    phonological, and semantic similarity to target
    phrases to provide comprehensive information about
    accuracy at different processing levels. The former
    three measures are automatically extractable,
    increasing objectivity, and the middle two are
    gradient, providing finer-grained information than
    traditionally used. We evaluate the measures in an
    English dictation task featuring phonetically reduced
    continuous speech. Whereas the lexical and
    orthographic measures emphasize listeners’ word
    identification difficulties, the phonological measure
    demonstrates that listeners can often still recover
    phonological features, and the semantic measure
    captures their ability to get the gist of the utterances.
    Correlational analyses and a discussion of practical
    and theoretical considerations show that combining
    multiple measures improves the dictation task’s
    utility as a research tool.
  • Felker, E. R., Ernestus, M., & Broersma, M. (2019). Lexically guided perceptual learning of a vowel shift in an interactive L2 listening context. In Proceedings of Interspeech 2019 (pp. 3123-3127). doi:10.21437/Interspeech.2019-1414.

    Abstract

    Lexically guided perceptual learning has traditionally been studied with ambiguous consonant sounds to which native listeners are exposed in a purely receptive listening context. To extend previous research, we investigate whether lexically guided learning applies to a vowel shift encountered by non-native listeners in an interactive dialogue. Dutch participants played a two-player game in English in either a control condition, which contained no evidence for a vowel shift, or a lexically constraining condition, in which onscreen lexical information required them to re-interpret their interlocutor’s /ɪ/ pronunciations as representing /ε/. A phonetic categorization pre-test and post-test were used to assess whether the game shifted listeners’ phonemic boundaries such that more of the /ε/-/ɪ/ continuum came to be perceived as /ε/. Both listener groups showed an overall post-test shift toward /ɪ/, suggesting that vowel perception may be sensitive to directional biases related to properties of the speaker’s vowel space. Importantly, listeners in the lexically constraining condition made relatively more post-test /ε/ responses than the control group, thereby exhibiting an effect of lexically guided adaptation. The results thus demonstrate that non-native listeners can adjust their phonemic boundaries on the basis of lexical information to accommodate a vowel shift learned in interactive conversation.
  • Fisher, S. E., & Tilot, A. K. (Eds.). (2019). Bridging senses: Novel insights from synaesthesia [Special Issue]. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 374.
  • Franken, M. K. (2018). Listening for speaking: Investigations of the relationship between speech perception and production. PhD Thesis, Radboud University, Nijmegen.

    Abstract

    Speaking and listening are complex tasks that we perform on a daily basis, almost without conscious effort. Interestingly, speaking almost never occurs without listening: whenever we speak, we at least hear our own speech. The research in this thesis is concerned with how the perception of our own speech influences our speaking behavior. We show that unconsciously, we actively monitor this auditory feedback of our own speech. This way, we can efficiently take action and adapt articulation when an error occurs and auditory feedback does not correspond to our expectation. Processing the auditory feedback of our speech does not, however, automatically affect speech production. It is subject to a number of constraints. For example, we do not just track auditory feedback, but also its consistency. If auditory feedback is more consistent over time, it has a stronger influence on speech production. In addition, we investigated how auditory feedback during speech is processed in the brain, using magnetoencephalography (MEG). The results suggest the involvement of a broad cortical network including both auditory and motor-related regions. This is consistent with the view that the auditory center of the brain is involved in comparing auditory feedback to our expectation of auditory feedback. If this comparison yields a mismatch, motor-related regions of the brain can be recruited to alter the ongoing articulations.

    Additional information

    full text via Radboud Repository
  • Frost, R. L. A., Isbilen, E. S., Christiansen, M. H., & Monaghan, P. (2019). Testing the limits of non-adjacent dependency learning: Statistical segmentation and generalisation across domains. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 1787-1793). Montreal, QB: Cognitive Science Society.

    Abstract

    Achieving linguistic proficiency requires identifying words from speech, and discovering the constraints that govern the way those words are used. In a recent study of non-adjacent dependency learning, Frost and Monaghan (2016) demonstrated that learners may perform these tasks together, using similar statistical processes - contrary to prior suggestions. However, in their study, non-adjacent dependencies were marked by phonological cues (plosive-continuant-plosive structure), which may have influenced learning. Here, we test the necessity of these cues by comparing learning across three conditions; fixed phonology, which contains these cues, varied phonology, which omits them, and shapes, which uses visual shape sequences to assess the generality of statistical processing for these tasks. Participants segmented the sequences and generalized the structure in both auditory conditions, but learning was best when phonological cues were present. Learning was around chance on both tasks for the visual shapes group, indicating statistical processing may critically differ across domains.
  • Galke, L., Gerstenkorn, G., & Scherp, A. (2018). A case study of closed-domain response suggestion with limited training data. In M. Elloumi, M. Granitzer, A. Hameurlain, C. Seifert, B. Stein, A. Min Tjoa, & R. Wagner (Eds.), Database and Expert Systems Applications: DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings (pp. 218-229). Cham, Switzerland: Springer.

    Abstract

    We analyze the problem of response suggestion in a closed domain along a real-world scenario of a digital library. We present a text-processing pipeline to generate question-answer pairs from chat transcripts. On this limited amount of training data, we compare retrieval-based, conditioned-generation, and dedicated representation learning approaches for response suggestion. Our results show that retrieval-based methods that strive to find similar, known contexts are preferable over parametric approaches from the conditioned-generation family, when the training data is limited. We, however, identify a specific representation learning approach that is competitive to the retrieval-based approaches despite the training data limitation.
  • Galke, L., Vagliano, I., & Scherp, A. (2019). Can graph neural networks go „online“? An analysis of pretraining and inference. In Proceedings of the Representation Learning on Graphs and Manifolds: ICLR2019 Workshop.

    Abstract

    Large-scale graph data in real-world applications is often not static but dynamic,
    i. e., new nodes and edges appear over time. Current graph convolution approaches
    are promising, especially, when all the graph’s nodes and edges are available dur-
    ing training. When unseen nodes and edges are inserted after training, it is not
    yet evaluated whether up-training or re-training from scratch is preferable. We
    construct an experimental setup, in which we insert previously unseen nodes and
    edges after training and conduct a limited amount of inference epochs. In this
    setup, we compare adapting pretrained graph neural networks against retraining
    from scratch. Our results show that pretrained models yield high accuracy scores
    on the unseen nodes and that pretraining is preferable over retraining from scratch.
    Our experiments represent a first step to evaluate and develop truly online variants
    of graph neural networks.
  • Galke, L., Melnychuk, T., Seidlmayer, E., Trog, S., Foerstner, K., Schultz, C., & Tochtermann, K. (2019). Inductive learning of concept representations from library-scale bibliographic corpora. In K. David, K. Geihs, M. Lange, & G. Stumme (Eds.), Informatik 2019: 50 Jahre Gesellschaft für Informatik - Informatik für Gesellschaft (pp. 219-232). Bonn: Gesellschaft für Informatik e.V. doi:10.18420/inf2019_26.
  • Galke, L., Mai, F., & Vagliano, I. (2018). Multi-modal adversarial autoencoders for recommendations of citations and subject labels. In T. Mitrovic, J. Zhang, L. Chen, & D. Chin (Eds.), UMAP '18: Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (pp. 197-205). New York: ACM. doi:10.1145/3209219.3209236.

    Abstract

    We present multi-modal adversarial autoencoders for recommendation and evaluate them on two different tasks: citation recommendation and subject label recommendation. We analyze the effects of adversarial regularization, sparsity, and different input modalities. By conducting 408 experiments, we show that adversarial regularization consistently improves the performance of autoencoders for recommendation. We demonstrate, however, that the two tasks differ in the semantics of item co-occurrence in the sense that item co-occurrence resembles relatedness in case of citations, yet implies diversity in case of subject labels. Our results reveal that supplying the partial item set as input is only helpful, when item co-occurrence resembles relatedness. When facing a new recommendation task it is therefore crucial to consider the semantics of item co-occurrence for the choice of an appropriate model.
  • Goldrick, M., Brehm, L., Pyeong Whan, C., & Smolensky, P. (2019). Transient blend states and discrete agreement-driven errors in sentence production. In G. J. Snover, M. Nelson, B. O'Connor, & J. Pater (Eds.), Proceedings of the Society for Computation in Linguistics (SCiL 2019) (pp. 375-376). doi:10.7275/n0b2-5305.
  • Goriot, C. (2019). Early-English education works no miracles: Cognitive and linguistic development in mainstream, early-English, and bilingual primary-school pupils in the Netherlands. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Hahn, L. E., Ten Buuren, M., De Nijs, M., Snijders, T. M., & Fikkert, P. (2019). Acquiring novel words in a second language through mutual play with child songs - The Noplica Energy Center. In L. Nijs, H. Van Regenmortel, & C. Arculus (Eds.), MERYC19 Counterpoints of the senses: Bodily experiences in musical learning (pp. 78-87). Ghent, Belgium: EuNet MERYC 2019.

    Abstract

    Child songs are a great source for linguistic learning. Here we explore whether children can acquire novel words in a second language by playing a game featuring child songs in a playhouse. We present data from three studies that serve as scientific proof for the functionality of one game of the playhouse: the Energy Center. For this game, three hand-bikes were mounted on a panel. When children start moving the hand-bikes, child songs start playing simultaneously. Once the children produce enough energy with the hand-bikes, the songs are additionally accompanied with the sounds of musical instruments. In our studies, children executed a picture-selection task to evaluate whether they acquired new vocabulary from the songs presented during the game. Two of our studies were run in the field, one at a Dutch and one at an Indian pre-school. The third study features data from a more controlled laboratory setting. Our results partly confirm that the Energy Center is a successful means to support vocabulary acquisition in a second language. More research with larger sample sizes and longer access to the Energy Center is needed to evaluate the overall functionality of the game. Based on informal observations at our test sites, however, we are certain that children do pick up linguistic content from the songs during play, as many of the children repeat words and phrases from songs they heard. We will pick up upon these promising observations during future studies
  • Heilbron, M., Ehinger, B., Hagoort, P., & De Lange, F. P. (2019). Tracking naturalistic linguistic predictions with deep neural language models. In Proceedings of the 2019 Conference on Cognitive Computational Neuroscience (pp. 424-427). doi:10.32470/CCN.2019.1096-0.

    Abstract

    Prediction in language has traditionally been studied using
    simple designs in which neural responses to expected
    and unexpected words are compared in a categorical
    fashion. However, these designs have been contested
    as being ‘prediction encouraging’, potentially exaggerating
    the importance of prediction in language understanding.
    A few recent studies have begun to address
    these worries by using model-based approaches to probe
    the effects of linguistic predictability in naturalistic stimuli
    (e.g. continuous narrative). However, these studies
    so far only looked at very local forms of prediction, using
    models that take no more than the prior two words into
    account when computing a word’s predictability. Here,
    we extend this approach using a state-of-the-art neural
    language model that can take roughly 500 times longer
    linguistic contexts into account. Predictability estimates
    fromthe neural network offer amuch better fit to EEG data
    from subjects listening to naturalistic narrative than simpler
    models, and reveal strong surprise responses akin to
    the P200 and N400. These results show that predictability
    effects in language are not a side-effect of simple designs,
    and demonstrate the practical use of recent advances
    in AI for the cognitive neuroscience of language.
  • Hill, C. (2018). Person reference and interaction in Umpila/Kuuku Ya'u narrative. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Hömke, P. (2019). The face in face-to-face communication: Signals of understanding and non-understanding. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Hopman, E., Thompson, B., Austerweil, J., & Lupyan, G. (2018). Predictors of L2 word learning accuracy: A big data investigation. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 513-518). Austin, TX: Cognitive Science Society.

    Abstract

    What makes some words harder to learn than others in a second language? Although some robust factors have been identified based on small scale experimental studies, many relevant factors are difficult to study in such experiments due to the amount of data necessary to test them. Here, we investigate what factors affect the ease of learning of a word in a second language using a large data set of users learning English as a second language through the Duolingo mobile app. In a regression analysis, we test and confirm the well-studied effect of cognate status on word learning accuracy. Furthermore, we find significant effects for both cross-linguistic semantic alignment and English semantic density, two novel predictors derived from large scale distributional models of lexical semantics. Finally, we provide data on several other psycholinguistically plausible word level predictors. We conclude with a discussion of the limits, benefits and future research potential of using big data for investigating second language learning.
  • Huettig, F., Kolinsky, R., & Lachmann, T. (Eds.). (2018). The effects of literacy on cognition and brain functioning [Special Issue]. Language, Cognition and Neuroscience, 33(3).
  • Isbilen, E., Frost, R. L. A., Monaghan, P., & Christiansen, M. (2018). Bridging artificial and natural language learning: Comparing processing- and reflection-based measures of learning. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1856-1861). Austin, TX: Cognitive Science Society.

    Abstract

    A common assumption in the cognitive sciences is that artificial and natural language learning rely on shared mechanisms. However, attempts to bridge the two have yielded ambiguous results. We suggest that an empirical disconnect between the computations employed during learning and the methods employed at test may explain these mixed results. Further, we propose statistically-based chunking as a potential computational link between artificial and natural language learning. We compare the acquisition of non-adjacent dependencies to that of natural language structure using two types of tasks: reflection-based 2AFC measures, and processing-based recall measures, the latter being more computationally analogous to the processes used during language acquisition. Our results demonstrate that task-type significantly influences the correlations observed between artificial and natural language acquisition, with reflection-based and processing-based measures correlating within – but not across – task-type. These findings have fundamental implications for artificial-to-natural language comparisons, both methodologically and theoretically.
  • Janse, E., & Quené, H. (1999). On the suitability of the cross-modal semantic priming task. In Proceedings of the XIVth International Congress of Phonetic Sciences (pp. 1937-1940).
  • Janssen, D. (1999). Producing past and plural inflections. PhD Thesis, Radboud University Nijmegen, Nijmegen. doi:10.17617/2.2057667.
  • Janssen, R., Moisik, S. R., & Dediu, D. (2018). Agent model reveals the influence of vocal tract anatomy on speech during ontogeny and glossogeny. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 171-174). Toruń, Poland: NCU Press. doi:10.12775/3991-1.042.
  • Janssen, R. (2018). Let the agents do the talking: On the influence of vocal tract anatomy no speech during ontogeny. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Joo, H., Jang, J., Kim, S., Cho, T., & Cutler, A. (2019). Prosodic structural effects on coarticulatory vowel nasalization in Australian English in comparison to American English. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 835-839). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    This study investigates effects of prosodic factors (prominence, boundary) on coarticulatory Vnasalization in Australian English (AusE) in CVN and NVC in comparison to those in American English
    (AmE). As in AmE, prominence was found to
    lengthen N, but to reduce V-nasalization, enhancing N’s nasality and V’s orality, respectively (paradigmatic contrast enhancement). But the prominence effect in CVN was more robust than that in AmE. Again similar to findings in AmE, boundary
    induced a reduction of N-duration and V-nasalization phrase-initially (syntagmatic contrast enhancement), and increased the nasality of both C and V phrasefinally.
    But AusE showed some differences in terms
    of the magnitude of V nasalization and N duration. The results suggest that the linguistic contrast enhancements underlie prosodic-structure modulation of coarticulatory V-nasalization in
    comparable ways across dialects, while the fine phonetic detail indicates that the phonetics-prosody interplay is internalized in the individual dialect’s phonetic grammar.
  • Kanero, J., Franko, I., Oranç, C., Uluşahin, O., Koskulu, S., Adigüzel, Z., Küntay, A. C., & Göksun, T. (2018). Who can benefit from robots? Effects of individual differences in robot-assisted language learning. In Proceedings of the 8th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) (pp. 212-217). Piscataway, NJ, USA: IEEE.

    Abstract

    It has been suggested that some individuals may benefit more from social robots than do others. Using second
    language (L2) as an example, the present study examined how individual differences in attitudes toward robots and personality
    traits may be related to learning outcomes. Preliminary results with 24 Turkish-speaking adults suggest that negative attitudes
    toward robots, more specifically thoughts and anxiety about the negative social impact that robots may have on the society,
    predicted how well adults learned L2 words from a social robot. The possible implications of the findings as well as future directions are also discussed
  • Kempen, G., & Hoenkamp, E. (1982). Incremental sentence generation: Implications for the structure of a syntactic processor. In J. Horecký (Ed.), COLING 82. Proceedings of the Ninth International Conference on Computational Linguistics, Prague, July 5-10, 1982 (pp. 151-156). Amsterdam: North-Holland.

    Abstract

    Human speakers often produce sentences incrementally. They can start speaking having in mind only a fragmentary idea of what they want to say, and while saying this they refine the contents underlying subsequent parts of the utterance. This capability imposes a number of constraints on the design of a syntactic processor. This paper explores these constraints and evaluates some recent computational sentence generators from the perspective of incremental production.
  • Kirsch, J. (2018). Listening for the WHAT and the HOW: Older adults' processing of semantic and affective information in speech. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Klein, W., & Musan, R. (Eds.). (1999). Das deutsche Perfekt [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (113).
  • Klein, W. (Ed.). (1982). Zweitspracherwerb [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (45).
  • Koch, X. (2018). Age and hearing loss effects on speech processing. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Kolipakam, V. (2018). A holistic approach to understanding pre-history. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Kung, C. (2018). Speech comprehension in a tone language: The role of lexical tone, context, and intonation in Cantonese-Chinese. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Lattenkamp, E. Z., Vernes, S. C., & Wiegrebe, L. (2018). Mammalian models for the study of vocal learning: A new paradigm in bats. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 235-237). Toruń, Poland: NCU Press. doi:10.12775/3991-1.056.
  • Lauscher, A., Eckert, K., Galke, L., Scherp, A., Rizvi, S. T. R., Ahmed, S., Dengel, A., Zumstein, P., & Klein, A. (2018). Linked open citation database: Enabling libraries to contribute to an open and interconnected citation graph. In J. Chen, M. A. Gonçalves, J. M. Allen, E. A. Fox, M.-Y. Kan, & V. Petras (Eds.), JCDL '18: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (pp. 109-118). New York: ACM. doi:10.1145/3197026.3197050.

    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.
  • Lefever, E., Hendrickx, I., Croijmans, I., Van den Bosch, A., & Majid, A. (2018). Discovering the language of wine reviews: A text mining account. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (pp. 3297-3302). Paris: LREC.

    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.
  • Levelt, W. J. M., & Plomp, R. (1962). Musical consonance and critical bandwidth. In Proceedings of the 4th International Congress Acoustics (pp. 55-55).
  • Liu, S., & Zhang, Y. (2019). Why some verbs are harder to learn than others – A micro-level analysis of everyday learning contexts for early verb learning. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 2173-2178). Montreal, QB: Cognitive Science Society.

    Abstract

    Verb learning is important for young children. While most
    previous research has focused on linguistic and conceptual
    challenges in early verb learning (e.g. Gentner, 1982, 2006),
    the present paper examined early verb learning at the
    attentional level and quantified the input for early verb learning
    by measuring verb-action co-occurrence statistics in parent-
    child interaction from the learner’s perspective. To do so, we
    used head-mounted eye tracking to record fine-grained
    multimodal behaviors during parent-infant joint play, and
    analyzed parent speech, parent and infant action, and infant
    attention at the moments when parents produced verb labels.
    Our results show great variability across different action verbs,
    in terms of frequency of verb utterances, frequency of
    corresponding actions related to verb meanings, and infants’
    attention to verbs and actions, which provide new insights on
    why some verbs are harder to learn than others.
  • Long, M. (2018). The lifelong interplay between language and cognition: From language learning to perspective-taking, new insights into the ageing mind. PhD Thesis, University of Edinburgh, Edinburgh.
  • Lopopolo, A., Frank, S. L., Van den Bosch, A., Nijhof, A., & Willems, R. M. (2018). The Narrative Brain Dataset (NBD), an fMRI dataset for the study of natural language processing in the brain. In B. Devereux, E. Shutova, & C.-R. Huang (Eds.), Proceedings of LREC 2018 Workshop "Linguistic and Neuro-Cognitive Resources (LiNCR) (pp. 8-11). Paris: LREC.

    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.
  • Lupyan, G., Wendorf, A., Berscia, L. M., & Paul, J. (2018). Core knowledge or language-augmented cognition? The case of geometric reasoning. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 252-254). Toruń, Poland: NCU Press. doi:10.12775/3991-1.062.
  • Mai, F., Galke, L., & Scherp, A. (2019). CBOW is not all you need: Combining CBOW with the compositional matrix space model. In Proceedings of the Seventh International Conference on Learning Representations (ICLR 2019). OpenReview.net.

    Abstract

    Continuous Bag of Words (CBOW) is a powerful text embedding method. Due to its strong capabilities to encode word content, CBOW embeddings perform well on a wide range of downstream tasks while being efficient to compute. However, CBOW is not capable of capturing the word order. The reason is that the computation of CBOW's word embeddings is commutative, i.e., embeddings of XYZ and ZYX are the same. In order to address this shortcoming, we propose a
    learning algorithm for the Continuous Matrix Space Model, which we call Continual Multiplication of Words (CMOW). Our algorithm is an adaptation of word2vec, so that it can be trained on large quantities of unlabeled text. We empirically show that CMOW better captures linguistic properties, but it is inferior to CBOW in memorizing word content. Motivated by these findings, we propose a hybrid model that combines the strengths of CBOW and CMOW. Our results show that the hybrid CBOW-CMOW-model retains CBOW's strong ability to memorize word content while at the same time substantially improving its ability to encode other linguistic information by 8%. As a result, the hybrid also performs better on 8 out of 11 supervised downstream tasks with an average improvement of 1.2%.
  • Mai, F., Galke, L., & Scherp, A. (2018). Using deep learning for title-based semantic subject indexing to reach competitive performance to full-text. In J. Chen, M. A. Gonçalves, J. M. Allen, E. A. Fox, M.-Y. Kan, & V. Petras (Eds.), JCDL '18: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (pp. 169-178). New York: ACM.

    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%.
  • Mainz, N. (2018). Vocabulary knowledge and learning: Individual differences in adult native speakers. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Mamus, E., Rissman, L., Majid, A., & Ozyurek, A. (2019). Effects of blindfolding on verbal and gestural expression of path in auditory motion events. In A. K. Goel, C. M. Seifert, & C. C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 2275-2281). Montreal, QB: Cognitive Science Society.

    Abstract

    Studies have claimed that blind people’s spatial representations are different from sighted people, and blind people display superior auditory processing. Due to the nature of auditory and haptic information, it has been proposed that blind people have spatial representations that are more sequential than sighted people. Even the temporary loss of sight—such as through blindfolding—can affect spatial representations, but not much research has been done on this topic. We compared blindfolded and sighted people’s linguistic spatial expressions and non-linguistic localization accuracy to test how blindfolding affects the representation of path in auditory motion events. We found that blindfolded people were as good as sighted people when localizing simple sounds, but they outperformed sighted people when localizing auditory motion events. Blindfolded people’s path related speech also included more sequential, and less holistic elements. Our results indicate that even temporary loss of sight influences spatial representations of auditory motion events
  • Marcoux, K., & Ernestus, M. (2019). Differences between native and non-native Lombard speech in terms of pitch range. In M. Ochmann, M. Vorländer, & J. Fels (Eds.), Proceedings of the ICA 2019 and EAA Euroregio. 23rd International Congress on Acoustics, integrating 4th EAA Euroregio 2019 (pp. 5713-5720). Berlin: Deutsche Gesellschaft für Akustik.

    Abstract

    Lombard speech, speech produced in noise, is acoustically different from speech produced in quiet (plain speech) in several ways, including having a higher and wider F0 range (pitch). Extensive research on native Lombard speech does not consider that non-natives experience a higher cognitive load while producing
    speech and that the native language may influence the non-native speech. We investigated pitch range in plain and Lombard speech in native and non-natives.
    Dutch and American-English speakers read contrastive question-answer pairs in quiet and in noise in English, while the Dutch also read Dutch sentence pairs. We found that Lombard speech is characterized by a wider pitch range than plain speech, for all speakers (native English, non-native English, and native Dutch).
    This shows that non-natives also widen their pitch range in Lombard speech. In sentences with early-focus, we see the same increase in pitch range when going from plain to Lombard speech in native and non-native English, but a smaller increase in native Dutch. In sentences with late-focus, we see the biggest increase for the native English, followed by non-native English and then native Dutch. Together these results indicate an effect of the native language on non-native Lombard speech.
  • Marcoux, K., & Ernestus, M. (2019). Pitch in native and non-native Lombard speech. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 2019) (pp. 2605-2609). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    Lombard speech, speech produced in noise, is
    typically produced with a higher fundamental
    frequency (F0, pitch) compared to speech in quiet. This paper examined the potential differences in native and non-native Lombard speech by analyzing median pitch in sentences with early- or late-focus produced in quiet and noise. We found an increase in pitch in late-focus sentences in noise for Dutch speakers in both English and Dutch, and for American-English speakers in English. These results
    show that non-native speakers produce Lombard speech, despite their higher cognitive load. For the early-focus sentences, we found a difference between the Dutch and the American-English speakers. Whereas the Dutch showed an increased F0 in noise
    in English and Dutch, the American-English speakers did not in English. Together, these results suggest that some acoustic characteristics of Lombard speech, such as pitch, may be language-specific, potentially
    resulting in the native language influencing the non-native Lombard speech.
  • Margetts, A. (1999). Valence and transitivity in Saliba: An Oceanic language of Papua New Guinea. PhD Thesis, Radboud University Nijmegen, Nijmegen. doi:10.17617/2.2057646.
  • Maslowski, M. (2019). Fast speech can sound slow: Effects of contextual speech rate on word recognition. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Merkx, D., Frank, S., & Ernestus, M. (2019). Language learning using speech to image retrieval. In Proceedings of Interspeech 2019 (pp. 1841-1845). doi:10.21437/Interspeech.2019-3067.

    Abstract

    Humans learn language by interaction with their environment and listening to other humans. It should also be possible for computational models to learn language directly from speech but so far most approaches require text. We improve on existing neural network approaches to create visually grounded embeddings for spoken utterances. Using a combination of a multi-layer GRU, importance sampling, cyclic learning rates, ensembling and vectorial self-attention our results show a remarkable increase in image-caption retrieval performance over previous work. Furthermore, we investigate which layers in the model learn to recognise words in the input. We find that deeper network layers are better at encoding word presence, although the final layer has slightly lower performance. This shows that our visually grounded sentence encoder learns to recognise words from the input even though it is not explicitly trained for word recognition.
  • Merkx, D., & Scharenborg, O. (2018). Articulatory feature classification using convolutional neural networks. In Proceedings of Interspeech 2018 (pp. 2142-2146). doi:10.21437/Interspeech.2018-2275.

    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.
  • Micklos, A., Macuch Silva, V., & Fay, N. (2018). The prevalence of repair in studies of language evolution. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 316-318). Toruń, Poland: NCU Press. doi:10.12775/3991-1.075.
  • Moisik, S. R., Zhi Yun, D. P., & Dediu, D. (2019). Active adjustment of the cervical spine during pitch production compensates for shape: The ArtiVarK study. In S. Calhoun, P. Escudero, M. Tabain, & P. Warren (Eds.), Proceedings of the 19th International Congress of Phonetic Sciences (ICPhS 20195) (pp. 864-868). Canberra, Australia: Australasian Speech Science and Technology Association Inc.

    Abstract

    The anterior lordosis of the cervical spine is thought
    to contribute to pitch (fo) production by influencing
    cricoid rotation as a function of larynx height. This
    study examines the matter of inter-individual
    variation in cervical spine shape and whether this has
    an influence on how fo is produced along increasing
    or decreasing scales, using the ArtiVarK dataset,
    which contains real-time MRI pitch production data.
    We find that the cervical spine actively participates in
    fo production, but the amount of displacement
    depends on individual shape. In general, anterior
    spine motion (tending toward cervical lordosis)
    occurs for low fo, while posterior movement (tending
    towards cervical kyphosis) occurs for high fo.
  • Mulder, K., Ten Bosch, L., & Boves, L. (2018). Analyzing EEG Signals in Auditory Speech Comprehension Using Temporal Response Functions and Generalized Additive Models. In Proceedings of Interspeech 2018 (pp. 1452-1456). doi:10.21437/Interspeech.2018-1676.

    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.
  • Nijveld, A., Ten Bosch, L., & Ernestus, M. (2019). ERP signal analysis with temporal resolution using a time window bank. In Proceedings of Interspeech 2019 (pp. 1208-1212). doi:10.21437/Interspeech.2019-2729.

    Abstract

    In order to study the cognitive processes underlying speech comprehension, neuro-physiological measures (e.g., EEG and MEG), or behavioural measures (e.g., reaction times and response accuracy) can be applied. Compared to behavioural measures, EEG signals can provide a more fine-grained and complementary view of the processes that take place during the unfolding of an auditory stimulus.

    EEG signals are often analysed after having chosen specific time windows, which are usually based on the temporal structure of ERP components expected to be sensitive to the experimental manipulation. However, as the timing of ERP components may vary between experiments, trials, and participants, such a-priori defined analysis time windows may significantly hamper the exploratory power of the analysis of components of interest. In this paper, we explore a wide-window analysis method applied to EEG signals collected in an auditory repetition priming experiment.

    This approach is based on a bank of temporal filters arranged along the time axis in combination with linear mixed effects modelling. Crucially, it permits a temporal decomposition of effects in a single comprehensive statistical model which captures the entire EEG trace.
  • Nijveld, A. (2019). The role of exemplars in speech comprehension. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Ostarek, M. (2018). Envisioning language: An exploration of perceptual processes in language comprehension. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Ozyurek, A., & Kita, S. (1999). Expressing manner and path in English and Turkish: Differences in speech, gesture, and conceptualization. In M. Hahn, & S. C. Stoness (Eds.), Proceedings of the Twenty-first Annual Conference of the Cognitive Science Society (pp. 507-512). London: Erlbaum.
  • Parhammer*, S. I., Ebersberg*, M., Tippmann*, J., Stärk*, K., Opitz, A., Hinger, B., & Rossi, S. (2019). The influence of distraction on speech processing: How selective is selective attention? In Proceedings of Interspeech 2019 (pp. 3093-3097). doi:10.21437/Interspeech.2019-2699.

    Abstract

    -* indicates shared first authorship -
    The present study investigated the effects of selective attention on the processing of morphosyntactic errors in unattended parts of speech. Two groups of German native (L1) speakers participated in the present study. Participants listened to sentences in which irregular verbs were manipulated in three different conditions (correct, incorrect but attested ablaut pattern, incorrect and crosslinguistically unattested ablaut pattern). In order to track fast dynamic neural reactions to the stimuli, electroencephalography was used. After each sentence, participants in Experiment 1 performed a semantic judgement task, which deliberately distracted the participants from the syntactic manipulations and directed their attention to the semantic content of the sentence. In Experiment 2, participants carried out a syntactic judgement task, which put their attention on the critical stimuli. The use of two different attentional tasks allowed for investigating the impact of selective attention on speech processing and whether morphosyntactic processing steps are performed automatically. In Experiment 2, the incorrect attested condition elicited a larger N400 component compared to the correct condition, whereas in Experiment 1 no differences between conditions were found. These results suggest that the processing of morphosyntactic violations in irregular verbs is not entirely automatic but seems to be strongly affected by selective attention.
  • Poort, E. D. (2019). The representation of cognates and interlingual homographs in the bilingual lexicon. PhD Thesis, University College London, London, UK.

    Abstract

    Cognates and interlingual homographs are words that exist in multiple languages. Cognates, like “wolf” in Dutch and English, also carry the same meaning. Interlingual homographs do not: the word “angel” in English refers to a spiritual being, but in Dutch to the sting of a bee. The six experiments included in this thesis examined how these words are represented in the bilingual mental lexicon. Experiment 1 and 2 investigated the issue of task effects on the processing of cognates. Bilinguals often process cognates more quickly than single-language control words (like “carrot”, which exists in English but not Dutch). These experiments showed that the size of this cognate facilitation effect depends on the other types of stimuli included in the task. These task effects were most likely due to response competition, indicating that cognates are subject to processes of facilitation and inhibition both within the lexicon and at the level of decision making. Experiment 3 and 4 examined whether seeing a cognate or interlingual homograph in one’s native language affects subsequent processing in one’s second language. This method was used to determine whether non-identical cognates share a form representation. These experiments were inconclusive: they revealed no effect of cross-lingual long-term priming. Most likely this was because a lexical decision task was used to probe an effect that is largely semantic in nature. Given these caveats to using lexical decision tasks, two final experiments used a semantic relatedness task instead. Both experiments revealed evidence for an interlingual homograph inhibition effect but no cognate facilitation effect. Furthermore, the second experiment found evidence for a small effect of cross-lingual long-term priming. After comparing these findings to the monolingual literature on semantic ambiguity resolution, this thesis concludes that it is necessary to explore the viability of a distributed connectionist account of the bilingual mental lexicon.

    Additional information

    full text via UCL
  • Pouw, W., Paxton, A., Harrison, S. J., & Dixon, J. A. (2019). Acoustic specification of upper limb movement in voicing. In A. Grimminger (Ed.), Proceedings of the 6th Gesture and Speech in Interaction – GESPIN 6 (pp. 68-74). Paderborn: Universitaetsbibliothek Paderborn. doi:10.17619/UNIPB/1-812.
  • Pouw, W., & Dixon, J. A. (2019). Quantifying gesture-speech synchrony. In A. Grimminger (Ed.), Proceedings of the 6th Gesture and Speech in Interaction – GESPIN 6 (pp. 75-80). Paderborn: Universitaetsbibliothek Paderborn. doi:10.17619/UNIPB/1-812.

    Abstract

    Spontaneously occurring speech is often seamlessly accompanied by hand gestures. Detailed
    observations of video data suggest that speech and gesture are tightly synchronized in time,
    consistent with a dynamic interplay between body and mind. However, spontaneous gesturespeech
    synchrony has rarely been objectively quantified beyond analyses of video data, which
    do not allow for identification of kinematic properties of gestures. Consequently, the point in
    gesture which is held to couple with speech, the so-called moment of “maximum effort”, has
    been variably equated with the peak velocity, peak acceleration, peak deceleration, or the onset
    of the gesture. In the current exploratory report, we provide novel evidence from motiontracking
    and acoustic data that peak velocity is closely aligned, and shortly leads, the peak pitch
    (F0) of speech

    Additional information

    https://osf.io/9843h/
  • Räsänen, O., Seshadri, S., & Casillas, M. (2018). Comparison of syllabification algorithms and training strategies for robust word count estimation across different languages and recording conditions. In Proceedings of Interspeech 2018 (pp. 1200-1204). doi:10.21437/Interspeech.2018-1047.

    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.
  • Ravignani, A., Garcia, M., Gross, S., de Reus, K., Hoeksema, N., Rubio-Garcia, A., & de Boer, B. (2018). Pinnipeds have something to say about speech and rhythm. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 399-401). Toruń, Poland: NCU Press. doi:10.12775/3991-1.095.
  • Raviv, L., Meyer, A. S., & Lev-Ari, S. (2018). The role of community size in the emergence of linguistic structure. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 402-404). Toruń, Poland: NCU Press. doi:10.12775/3991-1.096.
  • Rissman, L., & Majid, A. (2019). Agency drives category structure in instrumental events. In A. K. Goel, C. M. Seifert, & C. Freksa (Eds.), Proceedings of the 41st Annual Meeting of the Cognitive Science Society (CogSci 2019) (pp. 2661-2667). Montreal, QB: Cognitive Science Society.

    Abstract

    Thematic roles such as Agent and Instrument have a long-standing place in theories of event representation. Nonetheless, the structure of these categories has been difficult to determine. We investigated how instrumental events, such as someone slicing bread with a knife, are categorized in English. Speakers described a variety of typical and atypical instrumental events, and we determined the similarity structure of their descriptions using correspondence analysis. We found that events where the instrument is an extension of an intentional agent were most likely to elicit similar language, highlighting the importance of agency in structuring instrumental categories.
  • Rojas-Berscia, L. M. (2019). From Kawapanan to Shawi: Topics in language variation and change. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Rubio-Fernández, P., & Jara-Ettinger, J. (2018). Joint inferences of speakers’ beliefs and referents based on how they speak. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 991-996). Austin, TX: Cognitive Science Society.

    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.
  • Saleh, A., Beck, T., Galke, L., & Scherp, A. (2018). Performance comparison of ad-hoc retrieval models over full-text vs. titles of documents. In M. Dobreva, A. Hinze, & M. Žumer (Eds.), Maturity and Innovation in Digital Libraries: 20th International Conference on Asia-Pacific Digital Libraries, ICADL 2018, Hamilton, New Zealand, November 19-22, 2018, Proceedings (pp. 290-303). Cham, Switzerland: Springer.

    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.
  • Scharenborg, O., & Merkx, D. (2018). The role of articulatory feature representation quality in a computational model of human spoken-word recognition. In Proceedings of the Machine Learning in Speech and Language Processing Workshop (MLSLP 2018).

    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.
  • Schoenmakers, G.-J., & De Swart, P. (2019). Adverbial hurdles in Dutch scrambling. In A. Gattnar, R. Hörnig, M. Störzer, & S. Featherston (Eds.), Proceedings of Linguistic Evidence 2018: Experimental Data Drives Linguistic Theory (pp. 124-145). Tübingen: University of Tübingen.

    Abstract

    This paper addresses the role of the adverb in Dutch direct object scrambling constructions. We report four experiments in which we investigate whether the structural position and the scope sensitivity of the adverb affect acceptability judgments of scrambling constructions and native speakers' tendency to scramble definite objects. We conclude that the type of adverb plays a key role in Dutch word ordering preferences.

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