Sicurezza stradale: Proposta di traduzione di un estratto del research report "The Nature of Errors Made by Drivers"

The aim of this dissertation is to provide a translation from English into Italian of an extract from the research report “The Nature of Errors Made by Drivers”. The research was conducted by the MUARC (the Monash University Accident Research Centre) and published in June 2011 by Austroads, the association of Australasian road transport and traffic agencies. The excerpt chosen for translation is the third chapter, which provides an overview of the on-road pilot study conducted to analyse why drivers make mistakes during their everyday drive, including the methodology employed and the results obtained. This work is divided into six sections. It opens with an introduction on the topic and the formal structure of the report, followed by the first chapter, which provides an overview of the main features of the languages for special purposes and the specialised texts, an analysis of the text type and a presentation of the extract chosen for translation. In the second chapter the linguistic and extralinguistic resources available to specialised translators are presented, focussing on the ones used to translate the text. The third chapter is dedicated to the source text and its translation, while the fourth one provides an analysis of the strategies chosen to translate the text and a comment on the solutions to problematic passages. Finally, the last section – the conclusion – provides a comment on the entire work and on the professional activity of translators. The work closes with an appendix, which contains a glossary of the terms extracted from the translated text.

Estrazione terminologica automatica: sistemi a confronto

In any terminological study, candidate term extraction is a very time-consuming task. Corpus analysis tools have automatized some processes allowing the detection of relevant data within the texts, facilitating term candidate selection as well. Nevertheless, these tools are (normally) not specific for terminology research; therefore, the units which are automatically extracted need manual evaluation. Over the last few years some software products have been specifically developed for automatic term extraction. They are based on corpus analysis, but use linguistic and statistical information to filter data more precisely. As a result, the time needed for manual evaluation is reduced. In this framework, we tried to understand if and how these new tools can really be an advantage. In order to develop our project, we simulated a terminology study: we chose a domain (i.e. legal framework for medicinal products for human use) and compiled a corpus from which we extracted terms and phraseologisms using AntConc, a corpus analysis tool. Afterwards, we compared our list with the lists extracted automatically from three different tools (TermoStat Web, TaaS e Sketch Engine) in order to evaluate their performance. In the first chapter we describe some principles relating to terminology and phraseology in language for special purposes and show the advantages offered by corpus linguistics. In the second chapter we illustrate some of the main concepts of the domain selected, as well as some of the main features of legal texts. In the third chapter we describe automatic term extraction and the main criteria to evaluate it; moreover, we introduce the term-extraction tools used for this project. In the fourth chapter we describe our research method and, in the fifth chapter, we show our results and draw some preliminary conclusions on the performance and usefulness of term-extraction tools.