Abstract
We present classifiers that can accurately predict the proficiency level of nonnative Hebrew learners. This is important for practical (mainly educational) applications, but the endeavor also sheds light on the features that support the classification, thereby improving our understanding of learner language in general, and transfer effects from Arabic, French, and Russian on nonnative Hebrew in particular.
| Original language | English |
|---|---|
| Title of host publication | 2022 Language Resources and Evaluation Conference, LREC 2022 |
| Editors | Nicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, Stelios Piperidis |
| Publisher | European Language Resources Association (ELRA) |
| Pages | 5356-5365 |
| Number of pages | 10 |
| ISBN (Electronic) | 9791095546726 |
| State | Published - 2022 |
| Event | 13th International Conference on Language Resources and Evaluation Conference, LREC 2022 - Marseille, France Duration: 20 Jun 2022 → 25 Jun 2022 |
Publication series
| Name | 2022 Language Resources and Evaluation Conference, LREC 2022 |
|---|
Conference
| Conference | 13th International Conference on Language Resources and Evaluation Conference, LREC 2022 |
|---|---|
| Country/Territory | France |
| City | Marseille |
| Period | 20/06/22 → 25/06/22 |
Bibliographical note
Funding Information:We are grateful to the Israeli National Institute for Testing and Evaluation for making the essays available. We are very grateful to Noam Ordan for generously sharing his ideas with us in the initial stages of the project and for his advice and support throughout. Many thanks to Chen Gafni for his help with the Hebrew corpus and for providing useful comments. Thanks are also due to Anke Lüdeling, Anat Prior, Sarah Schneider and Dominique Bobeck for advice and fruitful discussions. This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 398186468 and by the Data Science Research Center at the University of Haifa.
Funding Information:
We are grateful to the Israeli National Institute for Testing and Evaluation for making the essays available. We are very grateful to Noam Ordan for generously sharing his ideas with us in the initial stages of the project and for his advice and support throughout. Many thanks to Chen Gafni for his help with the Hebrew corpus and for providing useful comments. Thanks are also due to Anke Lüdeling, Anat Prior, Sarah Schneider and Dominique Bobeck for advice and fruitful discussions. This work was funded by the Deutsche Forschungs-gemeinschaft (DFG, German Research Foundation) – 398186468 and by the Data Science Research Center at the University of Haifa.
Publisher Copyright:
© European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.
Keywords
- Hebrew
- Learner corpora
- Proficiency
ASJC Scopus subject areas
- Language and Linguistics
- Library and Information Sciences
- Linguistics and Language
- Education