Publications

Displaying 201 - 222 of 222
  • 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.
  • Thompson-Schill, S., Hagoort, P., Dominey, P. F., Honing, H., Koelsch, S., Ladd, D. R., Lerdahl, F., Levinson, S. C., & Steedman, M. (2013). Multiple levels of structure in language and music. In M. A. Arbib (Ed.), Language, music, and the brain: A mysterious relationship (pp. 289-303). Cambridge, MA: MIT Press.

    Abstract

    A forum devoted to the relationship between music and language begins with an implicit assumption: There is at least one common principle that is central to all human musical systems and all languages, but that is not characteristic of (most) other domains. Why else should these two categories be paired together for analysis? We propose that one candidate for a common principle is their structure. In this chapter, we explore the nature of that structure—and its consequences for psychological and neurological processing mechanisms—within and across these two domains.
  • 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 Valin Jr., R. D. (2013). Head-marking languages and linguistic theory. In B. Bickel, L. A. Grenoble, D. A. Peterson, & A. Timberlake (Eds.), Language typology and historical contingency: In honor of Johanna Nichols (pp. 91-124). Amsterdam: Benjamins.

    Abstract

    In her path-breaking 1986 paper, Johanna Nichols proposed a typological contrast between head-marking and dependent-marking languages. Nichols argues that even though the syntactic relations between the head and its dependents are the same in both types of language, the syntactic “bond” between them is not the same; in dependent-marking languages it is one of government, whereas in head-marking languages it is one of apposition. This distinction raises an important question for linguistic theory: How can this contrast – government versus apposition – which can show up in all of the major phrasal types in a language, be captured? The purpose of this paper is to explore the various approaches that have been taken in an attempt to capture the difference between head-marked and dependent-marked syntax in different linguistic theories. The basic problem that head-marking languages pose for syntactic theory will be presented, and then generative approaches will be discussed. The analysis of head-marked structure in Role and Reference Grammar will be presented
  • Van Valin Jr., R. D. (2013). Lexical representation, co-composition, and linking syntax and semantics. In J. Pustejovsky, P. Bouillon, H. Isahara, K. Kanzaki, & C. Lee (Eds.), Advances in generative lexicon theory (pp. 67-107). Dordrecht: Springer.
  • 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., & Fisher, S. E. (2013). Genetic pathways implicated in speech and language. In S. Helekar (Ed.), Animal models of speech and language disorders (pp. 13-40). New York: Springer. doi:10.1007/978-1-4614-8400-4_2.

    Abstract

    Disorders of speech and language are highly heritable, providing strong
    support for a genetic basis. However, the underlying genetic architecture is complex,
    involving multiple risk factors. This chapter begins by discussing genetic loci associated
    with common multifactorial language-related impairments and goes on to
    detail the only gene (known as FOXP2) to be directly implicated in a rare monogenic
    speech and language disorder. Although FOXP2 was initially uncovered in
    humans, model systems have been invaluable in progressing our understanding of
    the function of this gene and its associated pathways in language-related areas of the
    brain. Research in species from mouse to songbird has revealed effects of this gene
    on relevant behaviours including acquisition of motor skills and learned vocalisations
    and demonstrated a role for Foxp2 in neuronal connectivity and signalling,
    particularly in the striatum. Animal models have also facilitated the identification of
    wider neurogenetic networks thought to be involved in language development and
    disorder and allowed the investigation of new candidate genes for disorders involving
    language, such as CNTNAP2 and FOXP1. Ongoing work in animal models promises
    to yield new insights into the genetic and neural mechanisms underlying human
    speech and language
  • 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.
  • 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.
  • Windhouwer, M., Petro, J., Newskaya, I., Drude, S., Aristar-Dry, H., & Gippert, J. (2013). Creating a serialization of LMF: The experience of the RELISH project. In G. Francopoulo (Ed.), LMF - Lexical Markup Framework (pp. 215-226). London: Wiley.
  • Windhouwer, M., & Wright, S. E. (2013). LMF and the Data Category Registry: Principles and application. In G. Francopoulo (Ed.), LMF: Lexical Markup Framework (pp. 41-50). London: Wiley.
  • Wittenburg, P., & Ringersma, J. (2013). Metadata description for lexicons. In R. H. Gouws, U. Heid, W. Schweickard, & H. E. Wiegand (Eds.), Dictionaries: An international encyclopedia of lexicography: Supplementary volume: Recent developments with focus on electronic and computational lexicography (pp. 1329-1335). Berlin: Mouton de Gruyter.
  • Wright, S. E., Windhouwer, M., Schuurman, I., & Kemps-Snijders, M. (2013). Community efforts around the ISOcat Data Category Registry. In I. Gurevych, & J. Kim (Eds.), The People's Web meets NLP: Collaboratively constructed language resources (pp. 349-374). New York: Springer.

    Abstract

    The ISOcat Data Category Registry provides a community computing environment for creating, storing, retrieving, harmonizing and standardizing data category specifications (DCs), used to register linguistic terms used in various fields. This chapter recounts the history of DC documentation in TC 37, beginning from paper-based lists created for lexicographers and terminologists and progressing to the development of a web-based resource for a much broader range of users. While describing the considerable strides that have been made to collect a very large comprehensive collection of DCs, it also outlines difficulties that have arisen in developing a fully operative web-based computing environment for achieving consensus on data category names, definitions, and selections and describes efforts to overcome some of the present shortcomings and to establish positive working procedures designed to engage a wide range of people involved in the creation of language resources.
  • 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.
  • Zwitserlood, I., Perniss, P. M., & Ozyurek, A. (2013). Expression of multiple entities in Turkish Sign Language (TİD). In E. Arik (Ed.), Current Directions in Turkish Sign Language Research (pp. 272-302). Newcastle upon Tyne: Cambridge Scholars Publishing.

    Abstract

    This paper reports on an exploration of the ways in which multiple entities are expressed in Turkish Sign Language (TİD). The (descriptive and quantitative) analyses provided are based on a corpus of both spontaneous data and specifically elicited data, in order to provide as comprehensive an account as possible. We have found several devices in TİD for expression of multiple entities, in particular localization, spatial plural predicate inflection, and a specific form used to express multiple entities that are side by side in the same configuration (not reported for any other sign language to date), as well as numerals and quantifiers. In contrast to some other signed languages, TİD does not appear to have a productive system of plural reduplication. We argue that none of the devices encountered in the TİD data is a genuine plural marking device and that the plural interpretation of multiple entity localizations and plural predicate inflections is a by-product of the use of space to indicate the existence or the involvement in an event of multiple entities.

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