Araknion: inducción de modelos lingüísticos a partir de corpora

El proyecto Araknion tiene como objetivo general dotar al español y al catalán de una infraestructura básica de recursos lingüísticos para el procesamiento semántico de corpus en el marco de la Web 2.0 sean de origen oral o escrito.

Sports anglicisms in Spanish dictionaries and corpora

For references, please quote the full paper as published in the above journal.

Multilingual extension of a temporal expression normalizer using annotated corpora

This paper presents the automatic extension to other languages of TERSEO, a knowledge-based system for the recognition and normalization of temporal expressions originally developed for Spanish. TERSEO was first extended to English through the automatic translation of the temporal expressions. Then, an improved porting process was applied to Italian, where the automatic translation of the temporal expressions from English and from Spanish was combined with the extraction of new expressions from an Italian annotated corpus. Experimental results demonstrate how, while still adhering to the rule-based paradigm, the development of automatic rule translation procedures allowed us to minimize the effort required for porting to new languages. Relying on such procedures, and without any manual effort or previous knowledge of the target language, TERSEO recognizes and normalizes temporal expressions in Italian with good results (72% precision and 83% recall for recognition).

A reassessment of traditional lexicographical tools in the light of new corpora: sports Anglicisms in Spanish

There is no question nowadays as to the international and powerful status of English at a global scale and, consequently, as to its presence in non-English speaking countries at different levels. Linguistically speaking, English is one of the languages which have mostly influenced Spanish throughout its history and especially from the late 1960s. In this study, the impact of English on Spanish is considered in the language of sports; particularly, sports Anglicisms and false Anglicisms are analysed. Due attention is paid to the different forms that an Anglicism may adopt and to which of those forms are more widely accepted or rejected by prescriptivists and speakers at large, in the light of a contrastive analysis of their appearance in the Nuevo diccionario de anglicismos, the Diccionario de la Real Academia Española and the Corpus de Referencia del Español Actual.

Removing noisy mentions for distant supervision

Los métodos para Extracción de Información basados en la Supervisión a Distancia se basan en usar tuplas correctas para adquirir menciones de esas tuplas, y así entrenar un sistema tradicional de extracción de información supervisado. En este artículo analizamos las fuentes de ruido en las menciones, y exploramos métodos sencillos para filtrar menciones ruidosas. Los resultados demuestran que combinando el filtrado de tuplas por frecuencia, la información mutua y la eliminación de menciones lejos de los centroides de sus respectivas etiquetas mejora los resultados de dos modelos de extracción de información significativamente.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

The use of corpora as translation resources: A study based on a survey of Spanish professional translators

The aim of this paper is to describe the use that professional translators make of corpora as translation resources. First, we briefly review the literature on translation practitioners’ use of corpora in the contexts of both translation training and professional translation. Then we present our survey-based study, analyse the uptake of corpora among Spanish translators and describe the use of this kind of translation resource. The results show that even if corpora are not as frequently used as other kinds of resources, such as dictionaries, there are professional translators who do use corpora, in a variety of ways, in their work. Additionally, non-users do not seem entirely sceptical about corpora. Against that backdrop, translator trainers are invited to continue to report on how corpora can be used as translation resources.

A three-dimensional representation method for noisy point clouds based on growing self-organizing maps accelerated on GPUs

The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models, without considering time constraints. It is proposed a hardware implementation leveraging the computing power of modern GPUs, which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). The proposed methods were applied to different problem and applications in the area of computer vision such as the recognition and localization of objects, visual surveillance or 3D reconstruction.