Publications

Abstract

When people request information, they have a variety of means for eliciting the information. In English two of the primary resources for eliciting information include asking questions, making statements about their interlocutor (thereby generating confirmation or revision). But within these types there are a variety of ways that these information elicitors can be designed. The goal of this task is to examine how different languages seek and provide information, the extent to which syntax vs prosodic resources are used (e.g., in questions), and the extent to which the design of information seeking actions and their responses display a structural preference to promote social solidarity.

Abstract

“Dimensional expressions” single out and describe one symmetric axis of a 1D, 2D, or 3D object (e.g., The road is long). “Bloxes” is an interactive, object-matching task that elicits descriptions of dimensional contrasts between simple geometrical objects (rectangular blocks, rectangular boxes, and cylinders). The aim is to explore the linguistic encoding of dimensions, focusing on features of axis, orientation, flatness/solidity, size and shape. See also 'Suggestions for field research on dimensional expressions' (https://doi.org/10.17617/2.3003382).

Abstract

The aim of this task is to explore the linguistic expression of “dimensions” — e.g., the height, width or depth — of objects in the world around us. In a dimensional expression, one symmetric axis of a 1D, 2D, or 3D object is singled out and described (e.g., That man is tall). Dimensional expressions in different languages show a range of different combinatorial and extensional uses. This document guides the researcher through some spatial situations where contrastive features of dimensional expressions are likely to be observable.

Abstract

Natural human interaction involves the fast-paced exchange of speaker turns. Crucially, if a next speaker waited with planning their turn until the current speaker was finished, language production models would predict much longer turn transition times than what we observe. Next speakers must therefore prepare their turn in parallel to listening. Visual signals likely play a role in this process, for example by helping the next speaker to process the ongoing utterance and thus prepare an appropriately-timed response.

To understand how visual signals contribute to the timing of turn-taking, and to move beyond the mostly qualitative studies of gesture in conversation, we examined unconstrained, computer-mediated conversations between 20 pairs of participants while systematically manipulating speaker visibility. Using motion tracking and manual gesture annotation, we assessed 1) how visibility affected the timing of turn transitions, and 2) whether use of co-speech gestures and 3) the communicative kinematic features of these gestures were associated with changes in turn transition timing.

We found that 1) decreased visibility was associated with less tightly timed turn transitions, and 2) the presence of gestures was associated with more tightly timed turn transitions across visibility conditions. Finally, 3) structural and salient kinematics contributed to gesture’s facilitatory effect on turn transition times.

Our findings suggest that speaker visibility--and especially the presence and kinematic form of gestures--during conversation contributes to the temporal coordination of conversational turns in computer-mediated settings. Furthermore, our study demonstrates that it is possible to use naturalistic conversation and still obtain controlled results.

Abstract

This chapter explores grammatical gender as a linguistic phenomenon. First, I define gender in terms of agreement, and look at the parts of speech that can take gender agreement. Because it relates to assumptions underlying much psycholinguistic gender research, I also examine the reasons why gender systems are thought to emerge, change, and disappear. Then, I describe the gender system of Dutch. The frequent confusion about the number of genders in Dutch will be resolved by looking at the history of the system, and the role of pronominal reference therein. In addition, I report on three lexical- statistical analyses of the distribution of genders in the language. After having dealt with Dutch, I look at whether the genders of Dutch and other languages are more or less randomly assigned, or whether there is some system to it. In contrast to what many people think, regularities do indeed exist. Native speakers could in principle exploit such regularities to compute rather than memorize gender, at least in part. Although this should be taken into account as a possibility, I will also argue that it is by no means a necessary implication.

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.