Lucia Specia

Learning Structural Kernels for Natural Language Processing

2015 · White Rose Research Online (University of Leeds, The University of Sheffield, University of York)

Structural kernels are a flexible learning paradigm that has been widely used in Natural Language Processing. However, the problem of model selection in kernel-based methods is usually overlooked. Previous approaches mostly rely on setting default …

Joint Processing of Language and Visual Data for Better Automated Understanding (Dagstuhl Seminar 19021)

2019 · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

This report documents the program and the outcomes of Dagstuhl Seminar 19021 "Joint Processing of Language and Visual Data for Better Automated Understanding". It includes a discussion of the motivation and overall organization, the abstracts …

Exploring Supervised and Unsupervised Rewards in Machine Translation

2021

Reinforcement Learning (RL) is a powerful framework to address the discrepancy between loss functions used during training and the final evaluation metrics to be used at test time. When applied to neural Machine Translation (MT), …

What Makes a Scientific Paper be Accepted for Publication?

2021

Despite peer-reviewing being an essential component of academia since the 1600s, it has repeatedly received criticisms for lack of transparency and consistency. We posit that recent work in machine learning and explainable AI provide tools …

Findings of the 2015 Workshop on Statistical Machine Translation

2015

Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Barry Haddow, Matthias Huck, Chris Hokamp, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Carolina Scarton, Lucia Specia, Marco Turchi. Proceedings of the Tenth Workshop on Statistical …

Findings of the 2016 Conference on Machine Translation

2016

Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Martin Popel, Matt Post, Raphael Rubino, Carolina Scarton, …

Unsupervised Lexical Simplification for Non-Native Speakers

2016 · Proceedings of the AAAI Conference on Artificial Intelligence

Lexical Simplification is the task of replacing complex words with simpler alternatives. We propose a novel, unsupervised approach for the task. It relies on two resources: a corpus of subtitles and a new type of …

SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation

2017

Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, dialog and conversational systems. The STS shared task is a …

Lexical Simplification with Neural Ranking

2017

We present a new Lexical Simplification approach that exploits Neural Networks to learn substitutions from the Newsela corpus -a large set of professionally produced simplifications. We extract candidate substitutions by combining the Newsela corpus with …

Findings of the 2017 Conference on Machine Translation (WMT17)

2017

Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Shujian Huang, Matthias Huck, Philipp Koehn, Qun Liu, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Raphael Rubino, Lucia Specia, Marco Turchi. Proceedings of the …

How2: A Large-scale Dataset for Multimodal Language Understanding

2018 · arXiv (Cornell University)

In this paper, we introduce How2, a multimodal collection of instructional videos with English subtitles and crowdsourced Portuguese translations. We also present integrated sequence-to-sequence baselines for machine translation, automatic speech recognition, spoken language translation, and …

The IWSLT 2019 Evaluation Campaign

2019 · Research Publications (Maastricht University)

The IWSLT 2019 evaluation campaign featured three tasks: speech translation of (i) TED talks and (ii) How2 instructional videos from English into German and Portuguese, and (iii) text translation of TED talks from English into …

SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation

2017 · HAL (Le Centre pour la Communication Scientifique Directe)

Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, dialog and conversational systems. The STS shared task is a …