Abstract
This paper describes SYSTRAN participation to the Document-level Generation and Trans- lation (DGT) Shared Task of the 3rd Workshop on Neural Generation and Translation (WNGT 2019). We participate for the first time using a Transformer network enhanced with modified input embeddings and optimising an additional objective function that considers content selection. The network takes in structured data of basketball games and outputs a summary of the game in natural language.- Anthology ID:
- D19-5629
- Volume:
- Proceedings of the 3rd Workshop on Neural Generation and Translation
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong
- Editors:
- Alexandra Birch, Andrew Finch, Hiroaki Hayashi, Ioannis Konstas, Thang Luong, Graham Neubig, Yusuke Oda, Katsuhito Sudoh
- Venue:
- NGT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 262–267
- Language:
- URL:
- https://aclanthology.org/D19-5629
- DOI:
- 10.18653/v1/D19-5629
- Cite (ACL):
- Li Gong, Josep Crego, and Jean Senellart. 2019. SYSTRAN @ WNGT 2019: DGT Task. In Proceedings of the 3rd Workshop on Neural Generation and Translation, pages 262–267, Hong Kong. Association for Computational Linguistics.
- Cite (Informal):
- SYSTRAN @ WNGT 2019: DGT Task (Gong et al., NGT 2019)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/D19-5629.pdf