The NICT/ATR speech translation system for IWSLT 2007

Andrew Finch, Etienne Denoual, Hideo Okuma, Michael Paul, Hirofumi Yamamoto, Keiji Yasuda, Ruiqiang Zhang, Eiichiro Sumita


Abstract
This paper describes the NiCT-ATR statistical machine translation (SMT) system used for the IWSLT 2007 evaluation campaign. We participated in three of the four language pair translation tasks (CE, JE, and IE). We used a phrase-based SMT system using log-linear feature models for all tracks. This year we decoded from the ASR n-best lists in the JE track and found a gain in performance. We also applied some new techniques to facilitate the use of out-of-domain external resources by model combination and also by utilizing a huge corpus of n-grams provided by Google Inc.. Using these resources gave mixed results that depended on the technique also the language pair however, in some cases we achieved consistently positive results. The results from model-interpolation in particular were very promising.
Anthology ID:
2007.iwslt-1.15
Volume:
Proceedings of the Fourth International Workshop on Spoken Language Translation
Month:
October 15-16
Year:
2007
Address:
Trento, Italy
Venue:
IWSLT
SIG:
Publisher:
Note:
Pages:
Language:
URL:
https://aclanthology.org/2007.iwslt-1.15
DOI:
Bibkey:
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PDF:
https://aclanthology.org/2007.iwslt-1.15.pdf