Publications

Abstract

Language users process utterances by segmenting them into many cognitive units, which vary in their sizes and linguistic levels. Although we can do such unitization/segmentation easily, its cognitive mechanism is still not clear. This paper proposes an unsupervised model, Less-is-Better (LiB), to simulate the human cognitive process with respect to language unitization/segmentation. LiB follows the principle of least effort and aims to build a lexicon which minimizes the number of unit tokens (alleviating the effort of analysis) and number of unit types (alleviating the effort of storage) at the same time on any given corpus. LiB’s workflow is inspired by empirical cognitive phenomena. The design makes the mechanism of LiB cognitively plausible and the computational requirement light-weight. The lexicon generated by LiB performs the best among different types of lexicons (e.g. ground-truth words) both from an information-theoretical view and a cognitive view, which suggests that the LiB lexicon may be a plausible proxy of the mental lexicon.

Abstract

Automatic Language Identification of written texts is a well-established area of research in Computational Linguistics. State-of-the-art algorithms often rely on n-gram character models to identify the correct language of texts, with good results seen for European languages. In this paper we propose the use of a character n-gram model and a word n-gram language model for the automatic classification of two written varieties of Portuguese: European and Brazilian. Results reached 0.998 for accuracy using character 4-grams.

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.

Abstract

The purpose of this study is to shed light to the linguistic deficit in populations with dementia, and more specifically with Mild Cognitive Impairment and Alzheimer’s Disease; by examining the assignment of thematic roles (θ-roles) in sentences including psychological verbs.
The interest in types of dementia and its precursor is due to the relevance of the disease in present-day world society (Caloi, 2017). 47 millions of people worldwide were reported by the World Alzheimer Report in 2016 (Prince et al. 2016) as people with a type of dementia. This number surpasses the number of inhabitants in Spain, a whole country, and it is expected, according to the report, to triplicate until 2050 reaching the number of 131 million. The impact of this disease is observed not only at the social level but also in the economic one, because of their need for assistance in their everyday life. What is worrying, is the lack of total treatment once the disease has started. Despite the efforts of medicine, dementia is problematic in terms of its diagnosis, because a variety of cognitive abilities is assessed in combination with medical workup. Language is a crucial component in the procedure of diagnosis as linguistic deficits are among the first symptoms that accompany the onset of the disease. Therefore, further investigation of linguistic impairment is a necessity in order to enhance the diagnostic techniques used nowadays. Furthermore, the lack of efficient drugs for the treatment of the disease has necessitated the development of training programs for maintenance and increase of the cognitive abilities in people with either Mild Cognitive Impairment or a type of dementia …