Publications

Abstract

This contribution emphasizes the role of multimedia data not only for archiving languages but also for creating opportunities for innovative analyses. In the case at hand, video material was collected as part of the documentation of Akhoe Haiom, a Khoisan language spoken in northern Namibia. The multimedia documentation project brought together linguistic and anthropological work to highlight connections between specialized domains, namely kinship terminology, interrogatives and reciprocals. These connections would have gone unnoticed or undocumented in more conventional modes of language description. It is suggested that such an approach may be particularly appropriate for the documentation of endangered languages since it directs the focus of attention away from isolated traits of languages towards more complex practices of communication that are also frequently threatened with extinction.

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

The lexicons of many sign languages hold large proportions of “frozen” forms, viz. signs that are generally considered to have been formed productively (as classifier predicates), but that have diachronically undergone processes of lexicalisation. Nederlandse Gebarentaal (Sign Language of the Netherlands; henceforth: NGT) also has many of these signs (Van der Kooij 2002, Zwitserlood 2003). In contrast to the general view on “frozen” forms, a few researchers claim that these signs may be formed according to productive sign formation rules, notably Brennan (1990) for BSL, and Meir (2001, 2002) for ISL. Following these claims, I suggest an analysis of “frozen” NGT signs as morphologically complex, using the framework of Distributed Morphology. The signs in question are derived in a similar way as classifier predicates; hence their similar form (but diverging characteristics). I will indicate how and why the structure and use of classifier predicates and “frozen” forms differ. Although my analysis focuses on NGT, it may also be applicable to other sign languages.