| Téléchargement | - Voir la version finale : Improving cuneiform language identification with BERT (PDF, 292 Kio)
|
|---|
| DOI | Trouver le DOI : https://doi.org/10.18653/v1/W19-1402 |
|---|
| Auteur | Rechercher : Bernier-Colborne, Gabriel1; Rechercher : Goutte, Cyril1; Rechercher : Léger, Serge1 |
|---|
| Affiliation | - Conseil national de recherches du Canada. Technologies numériques
|
|---|
| Format | Texte, Article |
|---|
| Conférence | The Sixth Workshop on NLP for Similar Languages, Varieties and Dialects, 2019-6 - 2019-6, Ann Arbor, MI, USA |
|---|
| Résumé | We describe the systems developed by the National Research Council Canada for the Cuneiform Language Identification (CLI) shared task at the 2019 VarDial evaluation campaign. We compare a state-of-the-art baseline relying on character n-grams and a traditional statistical classifier, a voting ensemble of classifiers, and a deep learning approach using a Transformer network. We describe how these systems were trained, and analyze the impact of some preprocessing and model estimation decisions. The deep neural network achieved 77% accuracy on the test data, which turned out to be the best performance at the CLI evaluation, establishing a new state-of-the-art for cuneiform language identification. |
|---|
| Date de publication | 2019 |
|---|
| Maison d’édition | Association for Computational Linguistics |
|---|
| Dans | |
|---|
| Langue | anglais |
|---|
| Publications évaluées par des pairs | Oui |
|---|
| Exporter la notice | Exporter en format RIS |
|---|
| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
|---|
| Identificateur de l’enregistrement | e6334b65-1734-4c0e-86da-7fb23d5cf6be |
|---|
| Enregistrement créé | 2019-12-19 |
|---|
| Enregistrement modifié | 2020-05-30 |
|---|
