Publications

Abstract

How do languages encode different kinds of movement, and what features do people pay attention to when describing motion events? This document outlines topics concerning the investigation of “enter” and “exit” events. It helps contextualise research tasks that examine this domain (see 'Motion Elicitation' and 'Enter/Exit animation') and gives some pointers about what other questions can be explored.

Abstract

How do languages express ideas of movement, and how do they package features that can be part of motion, such as path and cause? This questionnaire is used to gain a picture of the lexical resources a language draws on for motion expressions. It targets issues of semantic conflation (i.e., what other semantic information besides motion may be encoded in a verb root) and patterns of semantic distribution (i.e., what types of information are encoded in the morphemes that come together to build a description of a motion event). It was originally designed for Australian languages, but has since been used around the world.

Abstract

Contrastive reference, where a speaker presents or identifies one item in explicit contrast to another (I like this book but that one is boring), has special communicative and information structure properties. This can be reflected in rules of demonstrative use. For example, in some languages, terms equivalent to this and that can be used for contrastive reference in almost any spatial context. But other two-term languages stick more closely to “distance rules” for demonstratives, allowing a this-like term in close space only. This task elicits data concerning one context of contrastive reference, focusing on whether (and how) non-proximal demonstratives can be used to distinguish objects within a proximal area. The task runs like a memory game, with the consultant being asked to identify the locations of two or three hidden items arranged within arm’s reach.

Abstract

How do languages encode different kinds of movement, and what features do people pay attention to when describing motion events? This task investigates the expression of “enter” and “exit” activities, that is, events involving motion in(to) and motion out (of) container-like items. The researcher first uses particular stimuli (a ball, a cup, rice, etc.) to elicit descriptions of enter/exit events from one consultant, and then asks another consultant to demonstrate the event based on these descriptions. See also the related entries Enter/Exit Animation and Background Questions for Enter/Exit Research.

Abstract

Demonstrative terms (e.g., this and that) are key to understanding how a language constructs and interprets spatial relationships. They are tricky to pin down, typically having functions that do not match “idealized” uses, and that can become invisible in narrow elicitation settings. This questionnaire is designed to identify the range(s) of use of certain spatial demonstrative terms, and help assess the roles played by gesture, access, attention, and addressee knowledge in demonstrative use. The stimuli consist of 25 diagrammed “elicitation settings” to be created by the researcher.

Abstract

Angelika Wittek untersuchte Zustandsveränderungsverben bei vier- bis sechsjährigen Kindern. Englischsprechende Kinder verstehen bis zum Alter von 8 Jahren diese Verben als Bewegungsverben und ignorieren, daß sie zusätzlich die Information über einen Endzustand im Sinne der Negation des Ausgangszustands beeinhalten. Wittek zeigte, daß entgegen der Erwartung transparente, morphologisch komplexe Formen (wachmachen), in denen die Partikel den Endzustand explizit macht, nicht besser verstanden werden als Simplizia (wecken). Zudem diskutierte sie, inwieweit die Verwendung des Adverbs wieder in restitutiver Lesart Hinweise auf den Erwerb dieser Verben geben kann.

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.

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.

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.