The TÜBİTAK statistical machine translation system for IWSLT 2012
Coşkun Mermer, Hamza Kaya, İlknur Durgar El-Kahlout, Mehmet Uğur Doğan
Abstract
WedescribetheTU ̈B ̇ITAKsubmissiontotheIWSLT2012 Evaluation Campaign. Our system development focused on utilizing Bayesian alignment methods such as variational Bayes and Gibbs sampling in addition to the standard GIZA++ alignments. The submitted tracks are the Arabic-English and Turkish-English TED Talks translation tasks.- Anthology ID:
- 2012.iwslt-evaluation.20
- Volume:
- Proceedings of the 9th International Workshop on Spoken Language Translation: Evaluation Campaign
- Month:
- December 6-7
- Year:
- 2012
- Address:
- Hong Kong, Table of contents
- Venue:
- IWSLT
- SIG:
- SIGSLT
- Publisher:
- Note:
- Pages:
- 144–148
- Language:
- URL:
- https://aclanthology.org/2012.iwslt-evaluation.20
- DOI:
- Cite (ACL):
- Coşkun Mermer, Hamza Kaya, İlknur Durgar El-Kahlout, and Mehmet Uğur Doğan. 2012. The TÜBİTAK statistical machine translation system for IWSLT 2012. In Proceedings of the 9th International Workshop on Spoken Language Translation: Evaluation Campaign, pages 144–148, Hong Kong, Table of contents.
- Cite (Informal):
- The TÜBİTAK statistical machine translation system for IWSLT 2012 (Mermer et al., IWSLT 2012)
- PDF:
- https://preview.aclanthology.org/autopr/2012.iwslt-evaluation.20.pdf