The RWTH Aachen speech recognition and machine translation system for IWSLT 2012

Stephan Peitz, Saab Mansour, Markus Freitag, Minwei Feng, Matthias Huck, Joern Wuebker, Malte Nuhn, Markus Nußbaum-Thom, Hermann Ney


Abstract
In this paper, the automatic speech recognition (ASR) and statistical machine translation (SMT) systems of RWTH Aachen University developed for the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2012 are presented. We participated in the ASR (English), MT (English-French, Arabic-English, Chinese-English, German-English) and SLT (English-French) tracks. For the MT track both hierarchical and phrase-based SMT decoders are applied. A number of different techniques are evaluated in the MT and SLT tracks, including domain adaptation via data selection, translation model interpolation, phrase training for hierarchical and phrase-based systems, additional reordering model, word class language model, various Arabic and Chinese segmentation methods, postprocessing of speech recognition output with an SMT system, and system combination. By application of these methods we can show considerable improvements over the respective baseline systems.
Anthology ID:
2012.iwslt-evaluation.7
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:
69–76
Language:
URL:
https://aclanthology.org/2012.iwslt-evaluation.7
DOI:
Bibkey:
Cite (ACL):
Stephan Peitz, Saab Mansour, Markus Freitag, Minwei Feng, Matthias Huck, Joern Wuebker, Malte Nuhn, Markus Nußbaum-Thom, and Hermann Ney. 2012. The RWTH Aachen speech recognition and machine translation system for IWSLT 2012. In Proceedings of the 9th International Workshop on Spoken Language Translation: Evaluation Campaign, pages 69–76, Hong Kong, Table of contents.
Cite (Informal):
The RWTH Aachen speech recognition and machine translation system for IWSLT 2012 (Peitz et al., IWSLT 2012)
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PDF:
https://aclanthology.org/2012.iwslt-evaluation.7.pdf