Akio Yokoo


2001

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ALT-J/C: a prototype Japanese-to-Chinese automatic language translation system
Minoru Hayashi | Setsuo Yamada | Akira Kataoka | Akio Yokoo
Proceedings of Machine Translation Summit VIII

This paper describes a prototype Japanese-to-Chinese automatic language translation system. ALT-J/C (Automatic Language Translator - Japanese-to-Chinese) is a semantic transfer based system, which is based on ALT-J/E (a Japanese-to-English system), but written to cope with Unicode. It is also designed to cope with constructions specific to Chinese. This system has the potential to become a framework for multilingual translation systems.

1999

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A new evaluation method for speech translation systems and a case study on ATR-MATRIX from Japanese to English
Toshiyuki Takezawa | Fumiaki Sugaya | Akio Yokoo | Seiichi Yamamoto
Proceedings of Machine Translation Summit VII

ATR-MATRIX is a multi-lingual speech-to-speech translation system designed to facilitate communications between two parties of different languages engaged in a spontaneous conversation in a travel arrangement domain. In this paper, we propose a new evaluation method for speech translation systems. Our current focus is on measuring the robustness of a language translation sub-system, with quick calculation and low cost. Therefore, we calculate the difference between the translation output from transcription texts and the translation output from input speech by a dynamic programming method. We present the first trial experiment of this method applied to our Japanese-to-English speech translation system. We also provide related discussions on such points as error analysis and the relationship between the proposed method and translation quality evaluation manually done by humans.

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An Efficient Statistical Speech Act Type Tagging System for Speech Translation Systems
Hideki Tanaka | Akio Yokoo
Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics

1998

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Context Management with Topics for Spoken Dialogue Systems
Kristiina Jokinen | Hideki Tanaka | Akio Yokoo
COLING 1998 Volume 1: The 17th International Conference on Computational Linguistics

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Planning Dialogue Contributions With New Information
Kristiina Jokinen | Hideki Tanaka | Akio Yokoo
Natural Language Generation

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Context Management with Topics for Spoken Dialogue Systems
Kristiina Jokinen | Hideki Tanaka | Akio Yokoo
36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, Volume 1

1994

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Two Methods for Learning ALT-J/E Translation Rules from Examples and a Semantic Hierarchy
Ilussein Allmuallim | Yasuhiro Akiba | Takefumi Yamazaki | Akio Yokoo | Shigeo Kaneda
COLING 1994 Volume 1: The 15th International Conference on Computational Linguistics

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A System of Verbal Semantic Attributes Focused on the Syntactic Correspondence between Japanese and English
Hiromi Nakaiwa | Akio Yokoo | Satoru Ikehara
COLING 1994 Volume 2: The 15th International Conference on Computational Linguistics

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Automatic Aquisition of Semantic Attributes for User Defined Words m Japanese to English Machine Translation
Satoru Ikehara | Satoshi Shirai | Akio Yokoo | Francis Bond | Yoshie Omi
Fourth Conference on Applied Natural Language Processing

1991

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Toward an MT System without Pre-Editing: Effects of a New Method in ALT-J/E
Satoru Ikehara | Satoshi Shirai | Akio Yokoo | Hiromi Nakaiwa
Proceedings of Machine Translation Summit III: Papers

Recently, several types of Japanese to English MT (machine translation) systems have been developed, but prior to using such systems, they have required a pre-editing process of re-writing the original text into Japanese that could be easily translated. For communication of translated information requiring speed in dissemination, application of these systems would necessarily pose problems. To overcome such problems, a Multi-Level Translation Method based on Constructive Process Theory had been proposed. In this paper, the benefits of this method in ALT-J/E will be described. In comparison with the conventional elementary composition method, the Multi-Level Translation Method, emphasizing the importance of the meaning contained in expression structures, has been ascertained to be capable of conducting translation according to meaning and context processing with comparative ease. We are now hopeful of realizing machine translation omitting the process of pre-editing.