Abstract
Research on speaker-adapted neural machine translation (NMT) is scarce. One of the main challenges for more personalized MT systems is finding large enough annotated parallel datasets with speaker information. Rabinovich et al. (2017) published an annotated parallel dataset for EN–FR and EN–DE, however, for many other language pairs no sufficiently large annotated datasets are available.- Anthology ID:
- 2018.eamt-main.59
- Volume:
- Proceedings of the 21st Annual Conference of the European Association for Machine Translation
- Month:
- May
- Year:
- 2018
- Address:
- Alicante, Spain
- Venue:
- EAMT
- SIG:
- Publisher:
- Note:
- Pages:
- 391
- Language:
- URL:
- https://aclanthology.org/2018.eamt-main.59
- DOI:
- Cite (ACL):
- Eva Vanmassenhove and Christian Hardmeier. 2018. Europarl Datasets with Demographic Speaker Information. In Proceedings of the 21st Annual Conference of the European Association for Machine Translation, page 391, Alicante, Spain.
- Cite (Informal):
- Europarl Datasets with Demographic Speaker Information (Vanmassenhove & Hardmeier, EAMT 2018)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2018.eamt-main.59.pdf