no code implementations • EMNLP 2021 • Eva Vanmassenhove, Chris Emmery, Dimitar Shterionov
Recent years have seen an increasing need for gender-neutral and inclusive language.
no code implementations • INLG (ACL) 2020 • Chris van der Lee, Chris Emmery, Sander Wubben, Emiel Krahmer
This paper describes the CACAPO dataset, built for training both neural pipeline and end-to-end data-to-text language generation systems.
1 code implementation • 13 Sep 2023 • Sergey Kramp, Giovanni Cassani, Chris Emmery
Native Language Identification (NLI) intends to classify an author's native language based on their writing in another language.
1 code implementation • 18 Apr 2023 • Javad PourMostafa Roshan Sharami, Dimitar Shterionov, Frédéric Blain, Eva Vanmassenhove, Mirella De Sisto, Chris Emmery, Pieter Spronck
While quality estimation (QE) can play an important role in the translation process, its effectiveness relies on the availability and quality of training data.
no code implementations • 10 Jan 2023 • Chris Emmery
This dissertation proposes a framework of user-centered security in Natural Language Processing (NLP), and demonstrates how it can improve the accessibility of related research.
no code implementations • 14 Jul 2022 • Chris van der Lee, Thiago castro Ferreira, Chris Emmery, Travis Wiltshire, Emiel Krahmer
In terms of output quality, extending the training set of a data-to-text system with a language model using the pseudo-labeling approach did increase text quality scores, but the data augmentation approach yielded similar scores to the system without training set extension.
1 code implementation • LREC 2022 • Chris Emmery, Ákos Kádár, Grzegorz Chrupała, Walter Daelemans
The perturbed data, models, and code are available for reproduction at https://github. com/cmry/augtox
no code implementations • 13 Sep 2021 • Eva Vanmassenhove, Chris Emmery, Dimitar Shterionov
Recent years have seen an increasing need for gender-neutral and inclusive language.
1 code implementation • EACL 2021 • Chris Emmery, Ákos Kádár, Grzegorz Chrupała
Written language contains stylistic cues that can be exploited to automatically infer a variety of potentially sensitive author information.
1 code implementation • 25 Oct 2019 • Chris Emmery, Ben Verhoeven, Guy De Pauw, Gilles Jacobs, Cynthia Van Hee, Els Lefever, Bart Desmet, Véronique Hoste, Walter Daelemans
The detection of online cyberbullying has seen an increase in societal importance, popularity in research, and available open data.
1 code implementation • COLING 2018 • Chris Emmery, Enrique Manjavacas, Grzegorz Chrupała
The task of obfuscating writing style using sequence models has previously been investigated under the framework of obfuscation-by-transfer, where the input text is explicitly rewritten in another style.
no code implementations • 17 Jan 2018 • Cynthia Van Hee, Gilles Jacobs, Chris Emmery, Bart Desmet, Els Lefever, Ben Verhoeven, Guy De Pauw, Walter Daelemans, Véronique Hoste
While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online.
no code implementations • WS 2017 • Chris Emmery, Grzegorz Chrupa{\l}a, Walter Daelemans
The majority of research on extracting missing user attributes from social media profiles use costly hand-annotated labels for supervised learning.
1 code implementation • LREC 2016 • Stéphan Tulkens, Chris Emmery, Walter Daelemans
With this research, we provide the embeddings themselves, the relation evaluation task benchmark for use in further research, and demonstrate how the benchmarked embeddings prove a useful unsupervised linguistic resource, effectively used in a downstream task.
no code implementations • LREC 2014 • Menno van Zaanen, Gerhard van Huyssteen, Suzanne Aussems, Chris Emmery, Roald Eiselen
Whereas in languages such as English the components that make up a compound are separated by a space, in languages such as Finnish, German, Afrikaans and Dutch these components are concatenated into one word.