Naoto Kato

Also published as: Naoto Katoh


Proper Name Machine Translation from Japanese to Japanese Sign Language
Taro Miyazaki | Naoto Kato | Seiki Inoue | Shuichi Umeda | Makiko Azuma | Nobuyuki Hiruma | Yuji Nagashima
Proceedings of the EMNLP’2014 Workshop on Language Technology for Closely Related Languages and Language Variants


Syntax-Driven Sentence Revision for Broadcast News Summarization
Hideki Tanaka | Akinori Kinoshita | Takeshi Kobayakawa | Tadashi Kumano | Naoto Katoh
Proceedings of the 2009 Workshop on Language Generation and Summarisation (UCNLG+Sum 2009)


A Syntactically Annotated Corpus of Japanese Spoken Monologue
Tomohiro Ohno | Shigeki Matsubara | Hideki Kashioka | Naoto Kato | Yasuyoshi Inagaki
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

Recently, monologue data such as lecture and commentary by professionals have been considered as valuable intellectual resources, and have been gathering attention. On the other hand, in order to use these monologue data effectively and efficiently, it is necessary for the monologue data not only just to be accumulated but also to be structured. This paper describes the construction of a Japanese spoken monologue corpus in which dependency structure is given to each utterance. Spontaneous monologue includes a lot of very long sentences composed of two or more clauses. In these sentences, there may exist the subject or the adverb common to multi-clauses, and it may be considered that the subject or adverb depend on multi-predicates. In order to give the dependency information in a real fashion, our research allows that a bunsetsu depends on multiple bunsetsus.


Probabilistic Model for Example-based Machine Translation
Eiji Aramaki | Sadao Kurohashi | Hideki Kashioka | Naoto Kato
Proceedings of Machine Translation Summit X: Papers

Example-based machine translation (EBMT) systems, so far, rely on heuristic measures in retrieving translation examples. Such a heuristic measure costs time to adjust, and might make its algorithm unclear. This paper presents a probabilistic model for EBMT. Under the proposed model, the system searches the translation example combination which has the highest probability. The proposed model clearly formalizes EBMT process. In addition, the model can naturally incorporate the context similarity of translation examples. The experimental results demonstrate that the proposed model has a slightly better translation quality than state-of-the-art EBMT systems.


Back Transliteration from Japanese to English using Target English Context
Isao Goto | Naoto Kato | Terumasa Ehara | Hideki Tanaka
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics


Transliteration considering context information based on the maximum entropy method
Isao Goto | Naoto Kato | Noriyoshi Uratani | Terumasa Ehara
Proceedings of Machine Translation Summit IX: Papers

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 different English words must often be converted into different katakana. To produce an adequate transliteration, the proposed method considers chunking of alphabetic letters of an English word into conversion units and considers English and Japanese context information simultaneously to calculate the plausibility of conversion. We have confirmed experimentally that the proposed method improves the conversion accuracy by 63% compared to a simple method that ignores the plausibility of chunking and contextual information.

A multi-language translation example browser
Isao Goto | Naoto Kato | Noriyoshi Uratani | Terumasa Ehara | Tadashi Kumano | Hideki Tanaka
Proceedings of Machine Translation Summit IX: System Presentations

This paper describes a Multi-language Translation Example Browser, a type of translation memory system. The system is able to retrieve translation examples from bilingual news databases, which consist of news transcripts of past broadcasts. We put a Japanese-English system to practical use and undertook trial operations of a system of eight language-pairs.


Statistical Method of Recognizing Local Cohesion
Naoto Katoh | Tsuyoshi Morimoto
COLING 1996 Volume 2: The 16th International Conference on Computational Linguistics


Machine Translation of Sentences with Fixed Expressions
Naoto Katoh | Teruaki Aizawa
Fourth Conference on Applied Natural Language Processing


A Machine Translation System for Foreign News in Satellite Broadcasting
Teruaki Aizawa | Terumasa Ehara | Noriyoshi Uratani | Hideki Tanaka | Naoto Kato | Sumio Nakase | Norikazu Aruga | Takeo Matsuda
COLING 1990 Volume 3: Papers presented to the 13th International Conference on Computational Linguistics