The MITLL-AFRL IWSLT 2016 Systems

Michaeel Kazi, Elizabeth Salesky, Brian Thompson, Jonathan Taylor, Jeremy Gwinnup, Timothy Anderson, Grant Erdmann, Eric Hansen, Brian Ore, Katherine Young, Michael Hutt


Abstract
This report summarizes the MITLL-AFRL MT and ASR systems and the experiments run during the 2016 IWSLT evaluation campaign. Building on lessons learned from previous years’ results, we refine our ASR systems and examine the explosion of neural machine translation systems and techniques developed in the past year. We experiment with a variety of phrase-based, hierarchical and neural-network approaches in machine translation and utilize system combination to create a composite system with the best characteristics of all attempted MT approaches.
Anthology ID:
2016.iwslt-1.21
Volume:
Proceedings of the 13th International Conference on Spoken Language Translation
Month:
December 8-9
Year:
2016
Address:
Seattle, Washington D.C
Venue:
IWSLT
SIG:
SIGSLT
Publisher:
International Workshop on Spoken Language Translation
Note:
Pages:
Language:
URL:
https://aclanthology.org/2016.iwslt-1.21
DOI:
Bibkey:
Cite (ACL):
Michaeel Kazi, Elizabeth Salesky, Brian Thompson, Jonathan Taylor, Jeremy Gwinnup, Timothy Anderson, Grant Erdmann, Eric Hansen, Brian Ore, Katherine Young, and Michael Hutt. 2016. The MITLL-AFRL IWSLT 2016 Systems. In Proceedings of the 13th International Conference on Spoken Language Translation, Seattle, Washington D.C. International Workshop on Spoken Language Translation.
Cite (Informal):
The MITLL-AFRL IWSLT 2016 Systems (Kazi et al., IWSLT 2016)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2016.iwslt-1.21.pdf
Data
WMT 2016