Hybrid language processing in the Spoken Language Translator

The paper presents an overview of the Spoken Language Translator (SLT) system's hybrid language-processing architecture, focussing on the way in which rule-based and statistical methods are combined to achieve robust and efficient performance within a linguistically motivated framework. In general, we argue that rules are desirable in order to encode domain-independent linguistic constraints and achieve high-quality grammatical output, while corpus-derived statistics are needed if systems are to be efficient and robust; further, that hybrid architectures are superior from the point of view of portability to architectures which only make use of one type of information. We address the topics of ``multi-engine'' strategies for robust translation; robust bottom-up parsing using pruning and grammar specialization; rational development of linguistic rule-sets using balanced domain corpora; and efficient supervised training by interactive disambiguation. All work described is fully implemented in the current version of the SLT-2 system.Comment: 4 pages, uses icassp97.sty; to appear in ICASSP-97; see http://www.cam.sri.com for related materia

Observations and Recommendations on the Internationalisation of Software

As computer programs enter the lives of more and more people worldwide, it is becoming increasingly unacceptable to assume that software with a user interface designed for an indigenous English speaking market will be acceptable outside its country of origin simply by changing the currency symbol. Developers of software who are serious about expanding sales into new markets must consider many issues when giving thought either to the creation of new software or the modification of existing software to work within the linguistic and cultural constraints of these new markets. The purpose of this paper is to examine the task of preparing software to be used in countries and cultures other than that in which it is created. We do this by reviewing some of the most important localisation issues that have been identified, and some of the tools and practices that are available to the software designer to deal with them. We shall also consider some of the areas of the software development process that are currently less well understood and supported. Our major emphasis is in non-graphical applications targeted at European markets. Keywords: Internationalisation, I18N, Localising, Enabling, Multi-lingual

European Arctic Initiatives Compendium

Julkaistu versi

A matter of words: NLP for quality evaluation of Wikipedia medical articles

Automatic quality evaluation of Web information is a task with many fields of applications and of great relevance, especially in critical domains like the medical one. We move from the intuition that the quality of content of medical Web documents is affected by features related with the specific domain. First, the usage of a specific vocabulary (Domain Informativeness); then, the adoption of specific codes (like those used in the infoboxes of Wikipedia articles) and the type of document (e.g., historical and technical ones). In this paper, we propose to leverage specific domain features to improve the results of the evaluation of Wikipedia medical articles. In particular, we evaluate the articles adopting an "actionable" model, whose features are related to the content of the articles, so that the model can also directly suggest strategies for improving a given article quality. We rely on Natural Language Processing (NLP) and dictionaries-based techniques in order to extract the bio-medical concepts in a text. We prove the effectiveness of our approach by classifying the medical articles of the Wikipedia Medicine Portal, which have been previously manually labeled by the Wiki Project team. The results of our experiments confirm that, by considering domain-oriented features, it is possible to obtain sensible improvements with respect to existing solutions, mainly for those articles that other approaches have less correctly classified. Other than being interesting by their own, the results call for further research in the area of domain specific features suitable for Web data quality assessment

Assessment and learning outcomes: the evaluation of deep learning in an on-line course

Using an online learning environment, students from European countries collaborated and communicated to carry out problem based learning in occupational therapy. The effectiveness of this approach was evaluated by means of the final assessments and published learning outcomes. In particular, transcripts from peer-to-peer sessions of synchronous communication were analysed. The SOLO taxonomy was used and the development of deep learning was studied week by week. This allowed the quality of the course to be appraised and showed, to a certain extent, the impact of this online international course on the learning strategies of the students. Results indicate that deep learning can be supported by synchronous communication and online meetings between course participants.</p