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This paper proposes a method of automatic transliteration from English to Japanese words. Our method successfully transliterates an English word not registered in any bilingual or pronunciation dictionaries by converting each partial letters in the English word into Japanese katakana characters. In such transliteration, identical letters occurring in(More)
This paper gives an overview of the Patent Machine Translation Task (PatentMT) at NTCIR-9 by describing the test collection, evaluation methods, and evaluation results. We organized three patent machine translation subtasks: Chi-nese to English, Japanese to English, and English to Japanese. For these subtasks, we provided large-scale test collections,(More)
Reordering is a difficult task in translating between widely different languages such as Japanese and English. We employ the post-ordering framework proposed by (Sudoh et al., 2011b) for Japanese to English translation and improve upon the reordering method. The existing post-ordering method reorders a sequence of target language words in a source language(More)
This paper proposes a method of automatic back transliteration of proper nouns, in which a Japanese transliterated-word is restored to the original English word. The English words are created from a sequence of letters; thus our method can create new English words that are not registered in dictionaries or English word lists. When a katakana character is(More)
This paper presents the results of the shared tasks from the 2nd workshop on Asian translation (WAT2015) including J↔E, J↔C scientific paper translation subtasks and C→J, K→J patent translation subtasks. For the WAT2015, 12 institutions participated in the shared tasks. About 500 translation results have been submitted to the automatic evaluation server,(More)
This paper presents the results of the 1st workshop on Asian translation (WMT2014) shared tasks, which included J↔E translation subtasks and J↔C translation subtasks. As the first year of WAT, 12 institutions participated to the shared tasks. More than 300 translation results have been submitted to the automatic evaluation server, and selected submissions(More)
This paper proposes new distortion models for phrase-based SMT. In decoding, a distortion model estimates the source word position to be translated next (NP) given the last translated source word position (CP). We propose a distortion model that can consider the word at the CP, a word at an NP candidate, and the context of the CP and the NP candidate(More)
Word reordering is a difficult task for translation between languages with widely different word orders, such as Japanese and English. A previously proposed post-ordering method for Japanese-to-English translation first translates a Japanese sentence into a sequence of English words in a word order similar to that of Japanese, then reorders the sequence(More)
Pulmonary tumor thrombotic microangiopathy (PTTM) is a fatal cancer-related pulmonary complication with rapidly progressing dyspnea, and occasionally induces sudden death. Here, we describe a postmortem-diagnosed PTTM case caused by gastric cancer, with the complaint of progressing dyspnea for 5 days.He did not have any abdominal symptoms or cancer history.(More)
Neural network language models, or continuous-space language models (CSLMs), have been shown to improve the performance of statistical machine translation (SMT) when they are used for reranking n-best translations. However, CSLMs have not been used in the first pass decoding of SMT, because using CSLMs in decoding takes a lot of time. In contrast, we(More)