Search Results for author: Anne Vilnat

Found 23 papers, 4 papers with code

Evaluating Tokenizers Impact on OOVs Representation with Transformers Models

1 code implementation LREC 2022 Alexandra Benamar, Cyril Grouin, Meryl Bothua, Anne Vilnat

Our experiments have led to exciting findings that showed: (1) It is easier to improve the representation of new words (A and B) than it is for words that already exist in the vocabulary of the Transformer models (C), (2) To ameliorate the representation of OOVs, the most effective method relies on adding external morpho-syntactic context rather than improving the semantic understanding of the words directly (fine-tuning) and (3) We cannot foresee the impact of minor misspellings in words because similar misspellings have different impacts on their representation.

Anatomy Domain Adaptation

Detecting Non-literal Translations by Fine-tuning Cross-lingual Pre-trained Language Models

1 code implementation COLING 2020 Yuming Zhai, Gabriel Illouz, Anne Vilnat

Human-generated non-literal translations reflect the richness of human languages and are sometimes indispensable to ensure adequacy and fluency.

Language Modelling Sentence +1

LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis

1 code implementation30 Aug 2020 Somnath Banerjee, Sahar Ghannay, Sophie Rosset, Anne Vilnat, Paolo Rosso

This paper describes the participation of LIMSI UPV team in SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text.

Sentiment Analysis

Classification automatique des proc\'ed\'es de traduction (Automatic Classification of Translation Processes)

no code implementations JEPTALNRECITAL 2019 Yuming Zhai, Gabriel Illouz, Anne Vilnat

En vue de distinguer la traduction litt{\'e}rale des autres proc{\'e}d{\'e}s de traduction, des traducteurs et linguistes ont propos{\'e} plusieurs typologies pour caract{\'e}riser les diff{\'e}rents proc{\'e}d{\'e}s de traduction, tels que l{'}{\'e}quivalence idiomatique, la g{\'e}n{\'e}ralisation, la particularisation, la modulation s{\'e}mantique, etc.

Classification General Classification +1

Construction of a Multilingual Corpus Annotated with Translation Relations

no code implementations COLING 2018 Yuming Zhai, Aur{\'e}lien Max, Anne Vilnat

Translation relations, which distinguish literal translation from other translation techniques, constitute an important subject of study for human translators (Chuquet and Paillard, 1989).

Machine Translation Paraphrase Generation +1

Bidirectionnal converter between syntactic annotations : from French Treebank Dependencies to PASSAGE annotations, and back

no code implementations LREC 2014 Munshi Asadullah, Patrick Paroubek, Anne Vilnat

We shall illustrate the mapping of important syntactic phenomena using the corpus made of the examples of the FTB - DEP annotation guidelines, which we have hand-annotated with PASSAGE annotations and used to compute quantitative performance measures on the FTB - DEP guidelines. n this paper we will briefly introduce the two annotation formats.

Construction and Annotation of a French Folkstale Corpus

no code implementations LREC 2014 Garcia-Fern, Anne ez, Anne-Laure Ligozat, Anne Vilnat

In this paper, we present the digitization and annotation of a tales corpus - which is to our knowledge the only French tales corpus available and classified according to the Aarne{\&}Thompson classification - composed of historical texts (with old French parts).

Emotion Recognition Information Retrieval +3

Event Nominals: Annotation Guidelines and a Manually Annotated Corpus in French

no code implementations LREC 2012 B{\'e}atrice Arnulphy, Xavier Tannier, Anne Vilnat

As our application domain is information extraction, we follow a named entity approach to describe and annotate events.

A contrastive review of paraphrase acquisition techniques

no code implementations LREC 2012 Houda Bouamor, Aur{\'e}lien Max, Gabriel Illouz, Anne Vilnat

This paper addresses the issue of what approach should be used for building a corpus of sententential paraphrases depending on one's requirements.

Information Retrieval Machine Translation

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