Objective: The aim of the work is to compare results research on oral language people with neurodegenerative diseases. On basis literature, and available information, methodologies in subject test are presented. Speech variables that have been considered studies were presented, including linguistic, phonetic phonological features, prosodic, acoustic, lexical, semantic, syntactic morpho-syntacti...

We show that generation of contextually appropriate syntactic variation can be improved using a model based on automatically extracted features. We adapt a model for predicting dative alternation from (Bresnan et al. 2005); this model incorporates lexical, syntactic, semantic and pragmatic features. We evaluate the effect of using different types of feature on this classification task and show ...

This paper describes our approaches to Native Language Identification (NLI) for the NLI shared task 2013. NLI as a sub area of author profiling focuses on identifying the first language of an author given a text in his second language. Researchers have reported several sets of features that have achieved relatively good performance in this task. The type of features used in such works are: lexi...

Selecting appropriate features to represent an entity pair plays a key role in the task of relation recognition. However, existing syntactic features or lexical features cannot capture the interaction between two entities because of the dearth of annotated relational corpus specialized for relation recognition. In this paper, we propose a semantic feature, called the latent topic feature, which...

TGermaCorp is a German text corpus whose primary sources are collected from German literature texts which date from the sixteenth century to the present. The corpus is intended to represent its target language (German) in syntactic, lexical, stylistic and chronological diversity. For this purpose, it is hand-annotated on several linguistic layers, including POS, lemma, named entities, multiword...

Joint morphological and syntactic analysis has been proposed as a way of improving parsing accuracy for richly inflected languages. Starting from a transition-based model for joint part-of-speech tagging and dependency parsing, we explore different ways of integrating morphological features into the model. We also investigate the use of rule-based morphological analyzers to provide hard or soft...

We study a novel architecture for syntactic SMT. In contrast to the dominant approach in the literature, the system does not rely on translation rules, but treat translation as an unconstrained target sentence generation task, using soft features to capture lexical and syntactic correspondences between the source and target languages. Target syntax features and bilingual translation features ar...