Search Results for author: Marta R. Costa-juss{\`a}

Found 30 papers, 0 papers with code

Multilingual and Interlingual Semantic Representations for Natural Language Processing: A Brief Introduction

no code implementations CL 2020 Marta R. Costa-juss{\`a}, Cristina Espa{\~n}a-Bonet, Pascale Fung, Noah A. Smith

We introduce the Computational Linguistics special issue on Multilingual and Interlingual Semantic Representations for Natural Language Processing.

Abusive language in Spanish children and young teenager's conversations: data preparation and short text classification with contextual word embeddings

no code implementations LREC 2020 Marta R. Costa-juss{\`a}, Esther Gonz{\'a}lez, Asuncion Moreno, Eudald Cumalat

We compare classical machine learning techniques to the use of a more ad-vanced model: the contextual word embeddings in the particular case of classification of abusive short-texts for the Spanishlanguage.

Abusive Language text-classification +2

BERT Masked Language Modeling for Co-reference Resolution

no code implementations WS 2019 Felipe Alfaro, Marta R. Costa-juss{\`a}, Jos{\'e} A. R. Fonollosa

This paper explains the TALP-UPC participation for the Gendered Pronoun Resolution shared-task of the 1st ACL Workshop on Gender Bias for Natural Language Processing.

General Classification Language Modelling +1

Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques

no code implementations WS 2019 Joel Escud{\'e} Font, Marta R. Costa-juss{\`a}

We take advantage of the fact that word embeddings are used in neural machine translation to propose a method to equalize gender biases in neural machine translation using these representations.

Fairness Machine Translation +2

Gendered Ambiguous Pronoun (GAP) Shared Task at the Gender Bias in NLP Workshop 2019

no code implementations WS 2019 Kellie Webster, Marta R. Costa-juss{\`a}, Christian Hardmeier, Will Radford

The 1st ACL workshop on Gender Bias in Natural Language Processing included a shared task on gendered ambiguous pronoun (GAP) resolution.

The TALP-UPC Machine Translation Systems for WMT18 News Shared Translation Task

no code implementations WS 2018 Noe Casas, Carlos Escolano, Marta R. Costa-juss{\`a}, Jos{\'e} A. R. Fonollosa

In this article we describe the TALP-UPC research group participation in the WMT18 news shared translation task for Finnish-English and Estonian-English within the multi-lingual subtrack.

Machine Translation Translation

Why Catalan-Spanish Neural Machine Translation? Analysis, comparison and combination with standard Rule and Phrase-based technologies

no code implementations WS 2017 Marta R. Costa-juss{\`a}

Given the recent appearance and popularity of neural MT, this paper analyzes the performance of this new approach compared to the well-established rule-based and phrase-based MT systems.

Machine Translation Translation

A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation

no code implementations LREC 2012 Eleftherios Avramidis, Marta R. Costa-juss{\`a}, Christian Federmann, Josef van Genabith, Maite Melero, Pavel Pecina

This corpus aims to serve as a basic resource for further research on whether hybrid machine translation algorithms and system combination techniques can benefit from additional (linguistically motivated, decoding, and runtime) information provided by the different systems involved.

Machine Translation Translation

BUCEADOR, a multi-language search engine for digital libraries

no code implementations LREC 2012 Jordi Adell, Antonio Bonafonte, Antonio Cardenal, Marta R. Costa-juss{\`a}, Jos{\'e} A. R. Fonollosa, Asunci{\'o}n Moreno, Eva Navas, Eduardo R. Banga

The paper presents the tool functionality, the architecture, the digital library and provide some information about the technology involved in the fields of automatic speech recognition, statistical machine translation, text-to-speech synthesis and information retrieval.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +7

The ML4HMT Workshop on Optimising the Division of Labour in Hybrid Machine Translation

no code implementations LREC 2012 Christian Federmann, Eleftherios Avramidis, Marta R. Costa-juss{\`a}, Josef van Genabith, Maite Melero, Pavel Pecina

We describe the “Shared Task on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid Machine Translation” (ML4HMT) which aims to foster research on improved system combination approaches for machine translation (MT).

Language Modelling Machine Translation +1

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