This paper describes ATR's hybrid approach to spoken language translation and it's application to the IWSLT 2005 translation task. Multiple corpus-based translation engines are used to translate the same input, whereby the best translation among the element MT outputs is selected according to statistical models. The evaluation results of the Japanese-to-English and Chinese-to-English translation tasks for different training data conditions showed the potential of the proposed hybrid approach and revealed new directions in how to improve the current system performance.
Cite as: Paul, M., Doi, T., Hwang, Y., Imamura, K., Okuma, H., Sumita, E. (2005) Nobody is perfect: ATR's hybrid approach to spoken language translation. Proc. International Workshop on Spoken Language Translation (IWSLT 2005), 45-52
@inproceedings{paul05_iwslt,
author={Michael Paul and Takao Doi and Youngsook Hwang and Kenji Imamura and Hideo Okuma and Eiichiro Sumita},
title={{Nobody is perfect: ATR's hybrid approach to spoken language translation}},
year=2005,
booktitle={Proc. International Workshop on Spoken Language Translation (IWSLT 2005)},
pages={45--52}
}