Jin'ichi Murakami

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In this paper, we consider signals originated from a sequence of sources. More specically, the problems of segmenting such signals and relating the segments to their sources are addressed. This issue has wide applications in many elds. This report describes a resolution method that is based on an Ergodic Hidden Markov Model (HMM), in which each HMM state(More)
We have evaluated the two-stage machine translation (MT) system. The first stage is a state-of-the-art trial rule-based machine translation system. The second stage is a normal statistical machine translation system. For Japanese-English machine translation , first, we used a Japanese-English rule-based MT, and we obtained "ENGLISH" sentences from Japanese(More)
In this study, we paid attention to the reliability of phrase table. We have been used the phrase table using Och's method[2]. And this method sometimes generate completely wrong phrase tables. We found that such phrase table caused by long parallel sentences. Therefore, we removed these long parallel sentences from training data. Also, we utilized general(More)
Our statistical machine translation system that uses large Japanese-English parallel sentences and long phrase tables is described. We collected 698,973 Japanese-English parallel sentences, and we used long phrase tables. Also, we utilized general tools for statistical machine translation , such as " Giza++ " [1], " moses " [2], and "(More)