A Multi-aligner for Japanese-Chinese Parallel Corpora

Yujie Zhang, Qun Liu, Qing Ma, Hitoshi Isahara


Abstract
Automatic word alignment is an important technology for extracting translation knowledge from parallel corpora. However, automatic techniques cannot resolve this problem completely because of variances in translations. We therefore need to investigate the performance potential of automatic word alignment and then decide how to suitably apply it. In this paper we first propose a lexical knowledge-based approach to word alignment on a Japanese-Chinese corpus. Then we evaluate the performance of the proposed approach on the corpus. At the same time we also apply a statistics-based approach, the well-known toolkit GIZA++, to the same test data. Through comparison of the performances of the two approaches, we propose a multi-aligner, exploiting the lexical knowledge-based aligner and the statistics-based aligner at the same time. Quantitative results confirmed the effectiveness of the multi-aligner.
Anthology ID:
2005.mtsummit-papers.18
Volume:
Proceedings of Machine Translation Summit X: Papers
Month:
September 13-15
Year:
2005
Address:
Phuket, Thailand
Venue:
MTSummit
SIG:
Publisher:
Note:
Pages:
133–140
Language:
URL:
https://aclanthology.org/2005.mtsummit-papers.18
DOI:
Bibkey:
Cite (ACL):
Yujie Zhang, Qun Liu, Qing Ma, and Hitoshi Isahara. 2005. A Multi-aligner for Japanese-Chinese Parallel Corpora. In Proceedings of Machine Translation Summit X: Papers, pages 133–140, Phuket, Thailand.
Cite (Informal):
A Multi-aligner for Japanese-Chinese Parallel Corpora (Zhang et al., MTSummit 2005)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/2005.mtsummit-papers.18.pdf