This paper introduces ATR's project named Corpus-Centered Computation (C3), which aims at developing a translation technology suitable for spoken language translation. C3 places corpora at the center of its technology. Translation knowledge is extracted from corpora, translation quality is gauged by referring to corpora, the best translation among multiple-engine outputs is selected based on corpora, and the corpora themselves are paraphrased or filtered by automated processes to improve the data quality on which translation engines are based. In particular, this paper reports the hybridization architecture of different machine translation systems, our technologies, their performance on the IWSLT04 task, and paraphrasing methods.