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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
| Publication date | 17/12/2021 |
|---|---|
| Host publication | Forum for Information Retrieval Evaluation (working notes) |
| Publisher | CEUR Workshop Proceedings |
| Pages | 273-282 |
| Number of pages | 10 |
| <mark>Original language</mark> | English |
| Event | 13th Annual Meeting of the Forum for Information Retrieval Evaluation - Duration: 13/12/2021 → 17/12/2021 |
| Conference | 13th Annual Meeting of the Forum for Information Retrieval Evaluation |
|---|---|
| Abbreviated title | FIRE |
| Period | 13/12/21 → 17/12/21 |
| Name | CEUR Workshop Proceedings |
|---|---|
| Publisher | CEUR-WS |
| Volume | 3159 |
| ISSN (Print) | 1613-0073 |
| Conference | 13th Annual Meeting of the Forum for Information Retrieval Evaluation |
|---|---|
| Abbreviated title | FIRE |
| Period | 13/12/21 → 17/12/21 |
This paper describes the WLV-RIT entry to the Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages (HASOC) shared task of 2021. The HASOC 2021 organizers provided participants with annotated datasets containing social media posts of English, Hindi and Marathi. We participated in Marathi Subtask 1A: identifying hateful, offensive and profane content. In our methodology, we take advantage of available data from high resource languages by applying cross-lingual transformer-based models and transfer learning to make predictions to Marathi data. Our system achieved a macro F1 score of 0.91 for the test set and it ranked 1 st place out of 25 systems.