Publications

Abstract

This study presents a new language identification model for pluricentric languages that uses n-gram language models at the character and word level. The model is evaluated in two steps. The first step consists of the identification of two varieties of Spanish (Argentina and Spain) and two varieties of French (Quebec and France) evaluated independently in binary classification schemes. The second step integrates these language models in a six-class classification with two Portuguese varieties.

Abstract

The book is a unique collection of research on sign languages that have emerged in rural communities with a high incidence of, often hereditary, deafness. These sign languages represent the latest addition to the comparative investigation of languages in the gestural modality, and the book is the first compilation of a substantial number of different "village sign languages".Written by leading experts in the field, the volume uniquely combines anthropological and linguistic insights, looking at both the social dynamics and the linguistic structures in these village communities. The book includes primary data from eleven different signing communities across the world, including results from Jamaica, India, Turkey, Thailand, and Bali. All known village sign languages are endangered, usually because of pressure from larger urban sign languages, and some have died out already. Ironically, it is often the success of the larger sign language communities in urban centres, their recognition and subsequent spread, which leads to the endangerment of these small minority sign languages. The book addresses this specific type of language endangerment, documentation strategies, and other ethical issues pertaining to these sign languages on the basis of first-hand experiences by Deaf fieldworkers

Abstract

To acquire the meaning of a verb, language learners not only need to find the correct mapping between a specific verb and an action or event in the world, but also infer the underlying relational meaning that the verb encodes. Most verb naming instances in naturalistic contexts are highly ambiguous as many possible actions can be embedded in the same scenario and many possible verbs can be used to describe those actions. To understand whether learners can find the correct verb meaning from referentially ambiguous learning situations, we conducted three experiments using the Human Simulation Paradigm with adult learners. Our results suggest that although finding the right verb meaning from one learning instance is hard, there is a statistical solution to this problem. When provided with multiple verb learning instances all referring to the same verb, learners are able to aggregate information across situations and gradually converge to the correct semantic space. Even in cases where they may not guess the exact target verb, they can still discover the right meaning by guessing a similar verb that is semantically close to the ground truth.