Publications

Displaying 101 - 137 of 137
  • Ravignani, A., Chiandetti, C., & Kotz, S. (2019). Rhythm and music in animal signals. In J. Choe (Ed.), Encyclopedia of Animal Behavior (vol. 1) (2nd ed., pp. 615-622). Amsterdam: Elsevier.
  • Roberts, S. G., Cuskley, C., McCrohon, L., Barceló-Coblijn, L., Feher, O., & Verhoef, T. (Eds.). (2016). The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11). doi:10.17617/2.2248195.
  • Rojas-Berscia, L. M. (2019). Nominalization in Shawi/Chayahuita. In R. Zariquiey, M. Shibatani, & D. W. Fleck (Eds.), Nominalization in languages of the Americas (pp. 491-514). Amsterdam: Benjamins.

    Abstract

    This paper deals with the Shawi nominalizing suffixes -su’~-ru’~-nu’ ‘general nominalizer’, -napi/-te’/-tun‘performer/agent nominalizer’, -pi’‘patient nominalizer’, and -nan ‘instrument nominalizer’. The goal of this article is to provide a description of nominalization in Shawi. Throughout this paper I apply the Generalized Scale Model (GSM) (Malchukov, 2006) to Shawi verbal nominalizations, with the intention of presenting a formal representation that will provide a basis for future areal and typological studies of nominalization. In addition, I dialogue with Shibatani’s model to see how the loss or gain of categories correlates with the lexical or grammatical nature of nominalizations. strong nominalization in Shawi correlates with lexical nominalization, whereas weak nominalizations correlate with grammatical nominalization. A typology which takes into account the productivity of the nominalizers is also discussed.
  • Rowland, C. F., & Kidd, E. (2019). Key issues and future directions: How do children acquire language? In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 181-185). Cambridge, MA: MIT Press.
  • Rubio-Fernández, P. (2019). Theory of mind. In C. Cummins, & N. Katsos (Eds.), The Handbook of Experimental Semantics and Pragmatics (pp. 524-536). Oxford: Oxford University Press.
  • Schapper, A., San Roque, L., & Hendery, R. (2016). Tree, firewood and fire in the languages of Sahul. In P. Juvonen (Ed.), The Lexical Typology of Semantic Shifts (pp. 355-422). Berlin: de Gruyter Mouton.
  • Senft, G. (2016). "Masawa - bogeokwa si tuta!": Cultural and cognitive implications of the Trobriand Islanders' gradual loss of their knowledge of how to make a masawa canoe. In P. Meusburger, T. Freytag, & L. Suarsana (Eds.), Ethnic and Cultural Dimensions of Knowledge (pp. 229-256). Heidelberg: Springer Verlag.

    Abstract

    This paper describes how the Trobriand Islanders of Papua New Guinea used to construct their big seagoing masawa canoes and how they used to make their sails, what forms of different knowledge and expertise they needed to do this during various stages of the construction processes, how this knowledge was socially distributed, and the social implications of all the joint communal activities that were necessary until a new canoe could be launched. Then it tries to answer the question why the complex distributed knowledge of how to make a masawa has been gradually getting lost in most of the village communities on the Trobriand Islands; and finally it outlines and discusses the implications of this loss for the Trobriand Islanders' culture, for their social construction of reality, and for their indigenous cognitive capacities.
  • Senft, G. (1998). 'Noble Savages' and the 'Islands of Love': Trobriand Islanders in 'Popular Publications'. In J. Wassmann (Ed.), Pacific answers to Western hegemony: Cultural practices of identity construction (pp. 119-140). Oxford: Berg Publishers.
  • Senft, G. (2019). Rituelle Kommunikation. In F. Liedtke, & A. Tuchen (Eds.), Handbuch Pragmatik (pp. 423-430). Stuttgart: J. B. Metzler. doi:10.1007/978-3-476-04624-6_41.

    Abstract

    Die Sprachwissenschaft hat den Begriff und das Konzept ›Rituelle Kommunikation‹ von der vergleichenden Verhaltensforschung übernommen. Humanethologen unterscheiden eine Reihe von sogenannten ›Ausdrucksbewegungen‹, die in der Mimik, der Gestik, der Personaldistanz (Proxemik) und der Körperhaltung (Kinesik) zum Ausdruck kommen. Viele dieser Ausdrucksbewegungen haben sich zu spezifischen Signalen entwickelt. Ethologen definieren Ritualisierung als Veränderung von Verhaltensweisen im Dienst der Signalbildung. Die zu Signalen ritualisierten Verhaltensweisen sind Rituale. Im Prinzip kann jede Verhaltensweise zu einem Signal werden, entweder im Laufe der Evolution oder durch Konventionen, die in einer bestimmten Gemeinschaft gültig sind, die solche Signale kulturell entwickelt hat und die von ihren Mitgliedern tradiert und gelernt werden.
  • Senft, G. (2016). Pragmatics. In K. B. Jensen, R. T. Craig, J. Pooley, & E. Rothenbuhler (Eds.), The International Encyclopedia of Communication Theory and Philosophy (pp. 1586-1598). Hoboken, NJ: John Wiley. doi:10.1002/9781118766804.wbiect165.

    Abstract

    This entry takes an interdisciplinary approach to linguistic pragmatics. It discusses how the meaning of utterances can only be understood in relation to overall cultural, social, and interpersonal contexts, as well as to culture-specific conventions and the speech events in which they are embedded. The entry discusses core issues of pragmatics such as speech act theory, conversational implicature, deixis, gesture, interaction strategies, ritual communication, phatic communion, linguistic relativity, ethnography of speaking, ethnomethodology, and conversation analysis. It takes a transdisciplinary view of the field, showing that linguistic pragmatics has its predecessors in other disciplines such as philosophy, psychology, ethology, ethnology, and sociology.
  • Senft, G. (1998). Zeichenkonzeptionen in Ozeanien. In R. Posner, T. Robering, & T.. Sebeok (Eds.), Semiotics: A handbook on the sign-theoretic foundations of nature and culture (Vol. 2) (pp. 1971-1976). Berlin: de Gruyter.
  • Seuren, P. A. M. (1988). Lexical meaning and presupposition. In W. Hüllen, & R. Schulze (Eds.), Understanding the lexicon: Meaning, sense and world knowledge in lexical semantics (pp. 170-187). Tübingen: Niemeyer.
  • Seuren, P. A. M. (1998). Towards a discourse-semantic account of donkey anaphora. In S. Botley, & T. McEnery (Eds.), New Approaches to Discourse Anaphora: Proceedings of the Second Colloquium on Discourse Anaphora and Anaphor Resolution (DAARC2) (pp. 212-220). Lancaster: Universiy Centre for Computer Corpus Research on Language, Lancaster University.
  • Silva, S., Petersson, K. M., & Castro, S. (2016). Rhythm in the brain: Is music special? In D. Da Silva Marques, & J. Avila-Toscano (Eds.), Neuroscience to neuropsychology: The study of the human brain (pp. 29-54). Barranquilla, Colombia: Ediciones CUR.
  • Sjerps, M. J., & Chang, E. F. (2019). The cortical processing of speech sounds in the temporal lobe. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 361-379). Cambridge, MA: MIT Press.
  • Skiba, R. (1988). Computer analysis of language data using the data transformation program TEXTWOLF in conjunction with a database system. In U. Jung (Ed.), Computers in applied linguistics and language teaching (pp. 155-159). Frankfurt am Main: Peter Lang.
  • Skiba, R. (1988). Computerunterstützte Analyse von sprachlichen Daten mit Hilfe des Datenumwandlungsprogramms TextWolf in Kombination mit einem Datenbanksystem. In B. Spillner (Ed.), Angewandte Linguistik und Computer (pp. 86-88). Tübingen: Gunter Narr.
  • Smith, A. C., Monaghan, P., & Huettig, F. (2016). Complex word recognition behaviour emerges from the richness of the word learning environment. In K. Twomey, A. C. Smith, G. Westermann, & P. Monaghan (Eds.), Neurocomputational Models of Cognitive Development and Processing: Proceedings of the 14th Neural Computation and Psychology Workshop (pp. 99-114). Singapore: World Scientific. doi:10.1142/9789814699341_0007.

    Abstract

    Computational models can reflect the complexity of human behaviour by implementing multiple constraints within their architecture, and/or by taking into account the variety and richness of the environment to which the human is responding. We explore the second alternative in a model of word recognition that learns to map spoken words to visual and semantic representations of the words’ concepts. Critically, we employ a phonological representation utilising coarse-coding of the auditory stream, to mimic early stages of language development that are not dependent on individual phonemes to be isolated in the input, which may be a consequence of literacy development. The model was tested at different stages during training, and was able to simulate key behavioural features of word recognition in children: a developing effect of semantic information as a consequence of language learning, and a small but earlier effect of phonological information on word processing. We additionally tested the role of visual information in word processing, generating predictions for behavioural studies, showing that visual information could have a larger effect than semantics on children’s performance, but that again this affects recognition later in word processing than phonological information. The model also provides further predictions for performance of a mature word recognition system in the absence of fine-coding of phonology, such as in adults who have low literacy skills. The model demonstrated that such phonological effects may be reduced but are still evident even when multiple distractors from various modalities are present in the listener’s environment. The model demonstrates that complexity in word recognition can emerge from a simple associative system responding to the interactions between multiple sources of information in the language learner’s environment.
  • Stolker, C. J. J. M., & Poletiek, F. H. (1998). Smartengeld - Wat zijn we eigenlijk aan het doen? Naar een juridische en psychologische evaluatie. In F. Stadermann (Ed.), Bewijs en letselschade (pp. 71-86). Lelystad, The Netherlands: Koninklijke Vermande.
  • Sumer, B., & Ozyurek, A. (2016). İşitme Engelli Çocukların Dil Edinimi [Sign language acquisition by deaf children]. In C. Aydin, T. Goksun, A. Kuntay, & D. Tahiroglu (Eds.), Aklın Çocuk Hali: Zihin Gelişimi Araştırmaları [Research on Cognitive Development] (pp. 365-388). Istanbul: Koc University Press.
  • Sumer, B. (2016). Scene-setting and reference introduction in sign and spoken languages: What does modality tell us? In B. Haznedar, & F. N. Ketrez (Eds.), The acquisition of Turkish in childhood (pp. 193-220). Amsterdam: Benjamins.

    Abstract

    Previous studies show that children do not become adult-like in learning to set the scene and introduce referents in their narrations until 9 years of age and even beyond. However, they investigated spoken languages, thus we do not know much about how these skills are acquired in sign languages, where events are expressed in visually similar ways to the real world events, unlike in spoken languages. The results of the current study demonstrate that deaf children (3;5–9;10 years) acquiring Turkish Sign Language, and hearing children (3;8–9;11 years) acquiring spoken Turkish both acquire scene-setting and referent introduction skills at similar ages. Thus the modality of the language being acquired does not have facilitating or hindering effects in the development of these skills.
  • Sumer, B., Zwitserlood, I., Perniss, P., & Ozyurek, A. (2016). Yer Bildiren İfadelerin Türkçe ve Türk İşaret Dili’nde (TİD) Çocuklar Tarafından Edinimi [The acqusition of spatial relations by children in Turkish and Turkish Sign Language (TID)]. In E. Arik (Ed.), Ellerle Konuşmak: Türk İşaret Dili Araştırmaları [Speaking with hands: Studies on Turkish Sign Language] (pp. 157-182). Istanbul: Koç University Press.
  • Suppes, P., Böttner, M., & Liang, L. (1998). Machine Learning of Physics Word Problems: A Preliminary Report. In A. Aliseda, R. van Glabbeek, & D. Westerståhl (Eds.), Computing Natural Language (pp. 141-154). Stanford, CA, USA: CSLI Publications.
  • Thomaz, A. L., Lieven, E., Cakmak, M., Chai, J. Y., Garrod, S., Gray, W. D., Levinson, S. C., Paiva, A., & Russwinkel, N. (2019). Interaction for task instruction and learning. In K. A. Gluck, & J. E. Laird (Eds.), Interactive task learning: Humans, robots, and agents acquiring new tasks through natural interactions (pp. 91-110). Cambridge, MA: MIT Press.
  • Twomey, K., Smith, A. C., Westermann, G., & Monaghan, P. (Eds.). (2016). Neurocomputational Models of Cognitive Development and Processing: Proceedings of the 14th Neural Computation and Psychology Workshop. Singapore: World Scientific.

    Abstract

    This volume presents peer-reviewed versions of papers presented at the 14th Neural Computation and Psychology Workshop (NCPW14), which took place in July 2014 at Lancaster University, UK. The workshop draws international attendees from the cutting edge of interdisciplinary
    research in psychology, computational modeling, artificial intelligence and psychology, and aims to drive forward
    our understanding of the mechanisms underlying a range of cognitive processes.
  • Van Leeuwen, T. M., & Dingemanse, M. (2022). Samenwerkende zintuigen. In S. Dekker, & H. Kause (Eds.), Wetenschappelijke doorbraken de klas in!: Geloven, Neustussenschot en Samenwerkende zintuigen (pp. 85-116). Nijmegen: Wetenschapsknooppunt Radboud Universiteit.

    Abstract

    Ook al hebben we het niet altijd door, onze zintuigen werken altijd samen. Als je iemand ziet praten, bijvoorbeeld, verwerken je hersenen automatisch tegelijkertijd het geluid van de woorden en de bewegingen van de lippen. Omdat onze zintuigen altijd samenwerken zijn onze hersenen erg gevoelig voor dingen die ‘samenhoren’ en goed bij elkaar passen. In dit hoofdstuk beschrijven we een project onderzoekend leren met als thema ‘Samenwerkende zintuigen’.
  • Van den Heuvel, H., Oostdijk, N., Rowland, C. F., & Trilsbeek, P. (2022). The CLARIN Knowledge Centre for Atypical Communication Expertise. In D. Fišer, & A. Witt (Eds.), CLARIN: The Infrastructure for Language Resources (pp. 373-388). Berlin, Boston: De Gruyter.

    Abstract

    In this chapter we introduce the CLARIN Knowledge Centre for Atypical Communication Expertise. The mission of ACE is to support researchers engaged in languages which pose particular challenges for analysis; for this, we use the umbrella term “atypical communication”. This includes language use by second-language learners, people with language disorders or those suffering from lan-guage disabilities, and languages that pose unique challenges for analysis, such as sign languages and languages spoken in a multilingual context. The chapter presents details about the collaborations and outreach of the centre, the services offered, and a number of showcases for its activities.
  • Van Valin Jr., R. D. (2016). An overview of information structure in three Amazonian languages. In M. Fernandez-Vest, & R. D. Van Valin Jr. (Eds.), Information structure and spoken language from a cross-linguistic perspective (pp. 77-92). Berlin: Mouton de Gruyter.
  • Van Berkum, J. J. A., & Nieuwland, M. S. (2019). A cognitive neuroscience perspective on language comprehension in context. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 429-442). Cambridge, MA: MIT Press.
  • Van Wijk, C., & Kempen, G. (1985). From sentence structure to intonation contour: An algorithm for computing pitch contours on the basis of sentence accents and syntactic structure. In B. Müller (Ed.), Sprachsynthese: Zur Synthese von natürlich gesprochener Sprache aus Texten und Konzepten (pp. 157-182). Hildesheim: Georg Olms.
  • Van Geenhoven, V. (1998). On the Argument Structure of some Noun Incorporating Verbs in West Greenlandic. In M. Butt, & W. Geuder (Eds.), The Projection of Arguments - Lexical and Compositional Factors (pp. 225-263). Stanford, CA, USA: CSLI Publications.
  • Van Valin Jr., R. D. (1998). The acquisition of WH-questions and the mechanisms of language acquisition. In M. Tomasello (Ed.), The new psychology of language: Cognitive and functional approaches to language structure (pp. 221-249). Mahwah, New Jersey: Erlbaum.
  • Vernes, S. C. (2019). Neuromolecular approaches to the study of language. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 577-593). Cambridge, MA: MIT Press.
  • Vessel, E. A., Ishizu, T., & Bignardi, G. (2022). Neural correlates of visual aesthetic appeal. In M. Skov, & M. Nadal (Eds.), The Routledge international handbook of neuroaesthetics (pp. 103-133). London: Routledge.
  • Weissenborn, J. (1988). Von der demonstratio ad oculos zur Deixis am Phantasma. Die Entwicklung der lokalen Referenz bei Kindern. In Karl Bühler's Theory of Language. Proceedings of the Conference held at Kirchberg, August 26, 1984 and Essen, November 21–24, 1984 (pp. 257-276). Amsterdam: Benjamins.
  • Zhang, Y., Chen, C.-h., & Yu, C. (2019). Mechanisms of cross-situational learning: Behavioral and computational evidence. In Advances in Child Development and Behavior; vol. 56 (pp. 37-63).

    Abstract

    Word learning happens in everyday contexts with many words and many potential referents for those words in view at the same time. It is challenging for young learners to find the correct referent upon hearing an unknown word at the moment. This problem of referential uncertainty has been deemed as the crux of early word learning (Quine, 1960). Recent empirical and computational studies have found support for a statistical solution to the problem termed cross-situational learning. Cross-situational learning allows learners to acquire word meanings across multiple exposures, despite each individual exposure is referentially uncertain. Recent empirical research shows that infants, children and adults rely on cross-situational learning to learn new words (Smith & Yu, 2008; Suanda, Mugwanya, & Namy, 2014; Yu & Smith, 2007). However, researchers have found evidence supporting two very different theoretical accounts of learning mechanisms: Hypothesis Testing (Gleitman, Cassidy, Nappa, Papafragou, & Trueswell, 2005; Markman, 1992) and Associative Learning (Frank, Goodman, & Tenenbaum, 2009; Yu & Smith, 2007). Hypothesis Testing is generally characterized as a form of learning in which a coherent hypothesis regarding a specific word-object mapping is formed often in conceptually constrained ways. The hypothesis will then be either accepted or rejected with additional evidence. However, proponents of the Associative Learning framework often characterize learning as aggregating information over time through implicit associative mechanisms. A learner acquires the meaning of a word when the association between the word and the referent becomes relatively strong. In this chapter, we consider these two psychological theories in the context of cross-situational word-referent learning. By reviewing recent empirical and cognitive modeling studies, our goal is to deepen our understanding of the underlying word learning mechanisms by examining and comparing the two theoretical learning accounts.
  • Zuidema, W., & Fitz, H. (2019). Key issues and future directions: Models of human language and speech processing. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 353-358). Cambridge, MA: MIT Press.

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