Paper

O objetivo deste trabalho é aplicar uma metodo- logia baseada na perplexidade, para calcular automa- ticamente a distância interlinguística entre diferentes períodos históricos de variantes diatópicas de idiomas.

This work describes the formalization of a word structure grammar that represents the complex morphological and morphosyntactic information embedded within the word forms of an agglutinative language (Basque), giving a comprehensive linguistic description of the main morphological phenomena, such as affixation, derivation, and composition, and also taking into account the modeling of both standard and non standard words. We have identified the relevant issues to be addressed in the representation of such a grammar.

Zero-shot learning is a very promising research topic. For a vision-based action recognition system, for instance, zero-shot learning allows to recognise actions never seen during the training phase. Previous works in zero-shot action recognition have exploited in several ways the visual appearance of input videos to infer actions. Here, we propose to add external knowledge to improve the performance of purely vision-based systems. Specifically, we have explored three different sources of knowledge in the form of text corpora.