Steven Neale

LX-DSemVectors: Distributional Semantics Models for Portuguese

In this article we describe the creation and distribution of the first publicly available word embeddings for Portuguese. Our embeddings are evaluated on their own and also compared with the original English models on a well-known analogy task. We gathered a large Portuguese corpus of 1.7 billion tokens, developed the first distributional semantic analogies test set for Portuguese, and proceeded with the first parametrization and evaluation of Portuguese word embeddings models.

SMT and Hybrid systems of the QTLeap project in the WMT16 IT-task

This paper presents the description of 12 systems submitted to the WMT16 IT-task, covering six different languages, namely Basque, Bulgarian, Dutch, Czech, Portuguese and Spanish. All these systems were developed under the scope of the QTLeap project, presenting a common strategy. For each language two different systems were submitted, namely a phrasebased MT system built using Moses, and a system exploiting deep language engineering approaches, that in all the languages but Bulgarian was implemented using TectoMT. For 4 of the 6 languages, the TectoMT-based system performs better than the Moses-based one.

Domain-Specific Hybrid Machine Translation from English to Portuguese

Machine translation (MT) from English to Portuguese has not typically received much attention in existing research. In this paper, we focus on MT from English to Portuguese for the specific domain of information technology (IT), building a small in-domain parallel corpus to address the lack of IT-specific and publicly-available parallel corpora and then adapted an existing hybrid MT system to the new language pair (English to Portuguese). We further improved the initial version of the EN-PT hybrid system by adding various modules to address the most frequently occurring errors in the initial system. In order to assess the improvements achieved by each of these dedicated modules, we compared all versions of our MT system automatically. In addition, we conduct and report on a detailed error analysis of the initial and final versions of our system.

Lexical Semantics Annotation for Enriched Portuguese Corpora

The semantic annotation of corpora has an important role to play in ensuring that sentences occurring in natural language texts are correctly understood based on their intended context. Two examples of lexical semantic units that contribute to this knowledge are word senses – which allow words with multiple meanings to be understood based on the context in which they are used – and named entities – which can be disambiguated and linked back to the specific encyclopedic resources that describe them.

Lexical semantics annotation for enriched Portuguese corpora

Autism Spectrum Disorder (ASD) often comprises difficulties in the acquisition of communication and language skills. Several researchers and companies have developed software to help individuals with ASD developing those skills; however, there is a lack of applications in Portuguese that are tailored to the individual needs of each child. In this context, we present VITHEA-Kids, a platform where caregivers can create exercises and customize the interaction between each child and the platform. We also developed a module for the automatic generation of multiple choice exercises, meant to be integrated in VITHEA-Kids. We evaluated this work with caregivers (which provided promising indicators), with a child (ongoing upon thesis delivery) and we also evaluated the generation of incorrect answers in multiple choice exercises (achieving acceptance rates between 61.11 % and 92.22 %).