Search Results for author: Maite Oronoz

Found 13 papers, 1 papers with code

Ixamed’s submission description for WMT20 Biomedical shared task: benefits and limitations of using terminologies for domain adaptation

no code implementations WMT (EMNLP) 2020 Xabier Soto, Olatz Perez-de-Viñaspre, Gorka Labaka, Maite Oronoz

Regarding the techniques used, we base on the findings from our previous works for translating clinical texts into Basque, making use of clinical terminology for adapting the MT systems to the clinical domain.

Domain Adaptation Machine Translation

Approximate Nearest Neighbour Extraction Techniques and Neural Networks for Suicide Risk Prediction in the CLPsych 2022 Shared Task

no code implementations NAACL (CLPsych) 2022 Hermenegildo Fabregat Marcos, Ander Cejudo, Juan Martinez-Romo, Alicia Perez, Lourdes Araujo, Nuria Lebea, Maite Oronoz, Arantza Casillas

This paper describes the participation of our group on the CLPsych 2022 shared task. For task A, which tries to capture changes in mood over time, we have applied an Approximate Nearest Neighbour (ANN) extraction technique with the aim of relabelling the user messages according to their proximity, based on the representation of these messages in a vector space.

Comparing and combining tagging with different decoding algorithms for back-translation in NMT: learnings from a low resource scenario

no code implementations EAMT 2022 Xabier Soto, Olatz Perez-de-Viñaspre, Gorka Labaka, Maite Oronoz

Recently, diverse approaches have been proposed to get better automatic evaluation results of NMT models using back-translation, including the use of sampling instead of beam search as decoding algorithm for creating the synthetic corpus.

Machine Translation NMT +2

IxaMed at PharmacoNER Challenge 2019

no code implementations WS 2019 Xabier Lahuerta, Iakes Goenaga, Koldo Gojenola, Aitziber Atutxa Salazar, Maite Oronoz

In order to identify named entities we have made use of a Bi-LSTM with a CRF on top in combination with different types of word embeddings.

Word Embeddings

The impact of simple feature engineering in multilingual medical NER

no code implementations WS 2016 Rebecka Weegar, Arantza Casillas, Arantza Diaz de Ilarraza, Maite Oronoz, Alicia P{\'e}rez, Koldo Gojenola

The goal of this paper is to examine the impact of simple feature engineering mechanisms before applying more sophisticated techniques to the task of medical NER.

Feature Engineering Lemmatization +3

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