Search Results for author: Luis Chiruzzo

Found 19 papers, 4 papers with code

Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches

no code implementations loresmt (COLING) 2022 Luis Chiruzzo, Euan McGill, Santiago Egea-Gómez, Horacio Saggion

This paper presents a series of experiments on translating between spoken Spanish and Spanish Sign Language glosses (LSE), including enriching Neural Machine Translation (NMT) systems with linguistic features, and creating synthetic data to pretrain and later on finetune a neural translation model.

Machine Translation NMT +1

Some strategies for the improvement of a Spanish WordNet

no code implementations GWC 2016 Matias Herrera, Javier Gonzalez, Luis Chiruzzo, Dina Wonsever

Although there are currently several versions of Princeton WordNet for different languages, the lack of development of some of these versions does not make it possible to use them in different Natural Language Processing applications.

Using Context to Improve the Spanish WordNet Translation

no code implementations GWC 2018 Alfonso Methol, Guillermo López, Juan Álvarez, Luis Chiruzzo, Dina Wonsever

We present some strategies for improving the Spanish version of WordNet, part of the MCR, selecting new lemmas for the Spanish synsets by translating the lemmas of the corresponding English synsets.

Translation

Experiments on a Guarani Corpus of News and Social Media

no code implementations NAACL (AmericasNLP) 2021 Santiago Góngora, Nicolás Giossa, Luis Chiruzzo

While Guarani is widely spoken in South America, obtaining a large amount of Guarani text from the web is hard.

Word Embeddings

Don't Take it Personally: Analyzing Gender and Age Differences in Ratings of Online Humor

no code implementations23 Aug 2022 J. A. Meaney, Steven R. Wilson, Luis Chiruzzo, Walid Magdy

Computational humor detection systems rarely model the subjectivity of humor responses, or consider alternative reactions to humor - namely offense.

Humor Detection

SemEval 2021 Task 7: HaHackathon, Detecting and Rating Humor and Offense

no code implementations SEMEVAL 2021 J. A. Meaney, Steven Wilson, Luis Chiruzzo, Adam Lopez, Walid Magdy

Our subtasks were binary humor detection, prediction of humor and offense ratings, and a novel controversy task: to predict if the variance in the humor ratings was higher than a specific threshold.

Humor Detection

Statistical Deep Parsing for Spanish Using Neural Networks

no code implementations WS 2020 Luis Chiruzzo, Dina Wonsever

This paper presents the development of a deep parser for Spanish that uses a HPSG grammar and returns trees that contain both syntactic and semantic information.

HAHA 2019 Dataset: A Corpus for Humor Analysis in Spanish

no code implementations LREC 2020 Luis Chiruzzo, Santiago Castro, Aiala Ros{\'a}

This paper presents the development of a corpus of 30, 000 Spanish tweets that were crowd-annotated with humor value and funniness score.

Development of a Guarani - Spanish Parallel Corpus

no code implementations LREC 2020 Luis Chiruzzo, Pedro Amarilla, Adolfo R{\'\i}os, Gustavo Gim{\'e}nez Lugo

This paper presents the development of a Guarani - Spanish parallel corpus with sentence-level alignment.

RETUYT in TASS 2017: Sentiment Analysis for Spanish Tweets using SVM and CNN

no code implementations17 Oct 2017 Aiala Rosá, Luis Chiruzzo, Mathias Etcheverry, Santiago Castro

This article presents classifiers based on SVM and Convolutional Neural Networks (CNN) for the TASS 2017 challenge on tweets sentiment analysis.

Sentiment Analysis Word Embeddings

A Crowd-Annotated Spanish Corpus for Humor Analysis

1 code implementation WS 2018 Santiago Castro, Luis Chiruzzo, Aiala Rosá, Diego Garat, Guillermo Moncecchi

Computational Humor involves several tasks, such as humor recognition, humor generation, and humor scoring, for which it is useful to have human-curated data.

Humor Detection

What Sentence are you Referring to and Why? Identifying Cited Sentences in Scientific Literature

no code implementations RANLP 2017 Ahmed Abura{'}ed, Luis Chiruzzo, Horacio Saggion

Current citation networks, which link papers by citation relationships (reference and citing paper), are useful to quantitatively understand the value of a piece of scientific work, however they are limited in that they do not provide information about what specific part of the reference paper the citing paper is referring to.

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