Publications

Abstract

The human language processor is conceived as a system that consists of several interrelated subsystems. Each subsystem performs a specific task in the complex process of language comprehension and production. A subsystem receives a particular input, performs certain specific operations on this input and yields a particular output. The subsystems can be characterized in terms of the transformations that relate the input representations to the output representations. An important issue in describing the language processing system is to identify the subsystems and to specify the relations between the subsystems. These relations can be conceived in two different ways. In one conception the subsystems are autonomous. They are related to each other only by the input-output channels. The operations in one subsystem are not affected by another system. The subsystems are modular, that is they are independent. In the other conception, the different subsystems influence each other. A subsystem affects the processes in another subsystem. In this conception there is an interaction between the subsystems.

Abstract

Our bodily experiences play an important role in the way that we think and speak. Abstract language is, however, difficult to reconcile with this body-centred view, unless we appreciate the role metaphors play. To explore the role of the senses across semantic domains, we focus on perception metaphors, and examine their realisation across diverse languages, methods, and approaches. To what extent do mappings in perception metaphor adhere to predictions based on our biological propensities; and to what extent is there space for cross-linguistic and cross-cultural variation? We find that while some metaphors have widespread commonality, there is more diversity attested than should be comfortable for universalist accounts.

Abstract

Language production involves the retrieval of information from memory, the planning of an articulatory program, and executive control and self-monitoring. These processes can be related to the domains of long-term memory, motor control, and executive control. Here, we argue that studying neuronal oscillations provides an important opportunity to understand how general neuronal computational principles support language production, also helping elucidate relationships between language and other domains of cognition. For each relevant domain, we provide a brief review of the findings in the literature with respect to neuronal oscillations. Then, we show how similar patterns are found in the domain of language production, both through review of previous literature and novel findings. We conclude that neurophysiological mechanisms, as reflected in modulations of neuronal oscillations, may act as a fundamental basis for bringing together and enriching the fields of language and cognition.

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.

Abstract

Conversation analysis (CA) is an approach to the study of language and social interaction that puts at center stage its sequential development. The chain of initiating and responding actions that characterizes any interaction is a source of internal evidence for the meaning of social behavior as it exposes the understandings that participants themselves give of what one another is doing. Such an analysis requires the close and repeated inspection of audio and video recordings of naturally occurring interaction, supported by transcripts and other forms of annotation. Distributional regularities are complemented by a demonstration of participants' orientation to deviant behavior. CA has long maintained a constructive dialogue and reciprocal influence with linguistic anthropology. This includes a recent convergence on the cross-linguistic and cross-cultural study of social interaction.

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.

Abstract

Incremental sentence generation imposes special constraints on the representation of the grammar and the design of the formulator (the module which is responsible for constructing the syntactic and morphological structure). In the model of natural speech production presented here, a formalism called Segment Grammar is used for the representation of linguistic knowledge. We give a definition of this formalism and present a formulator design which relies on it. Next, we present an object- oriented implementation of Segment Grammar. Finally, we compare Segment Grammar with other formalisms.

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

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.