activity
19992001
collaborators

5 papers

cs.CL2001

Using a Support-Vector Machine for Japanese-to-English Translation of Tense, Aspect, and Modality

Masaki Murata, Kiyotaka Uchimoto, Qing Ma +1

This paper describes experiments carried out using a variety of machine-learning methods, including the k-nearest neighborhood method that was used in a previous study, for the tra…

cs.CL2001

Correction of Errors in a Modality Corpus Used for Machine Translation by Using Machine-learning Method

Masaki Murata, Masao Utiyama, Kiyotaka Uchimoto +2

We performed corpus correction on a modality corpus for machine translation by using such machine-learning methods as the maximum-entropy method. We thus constructed a high-quality…

cs.CL2001

A Machine-Learning Approach to Estimating the Referential Properties of Japanese Noun Phrases

Masaki Murata, Kiyotaka Uchimoto, Qing Ma +1

The referential properties of noun phrases in the Japanese language, which has no articles, are useful for article generation in Japanese-English machine translation and for anapho…

cs.CL2000

Bunsetsu Identification Using Category-Exclusive Rules

Masaki Murata, Kiyotaka Uchimoto, Qing Ma +1

This paper describes two new bunsetsu identification methods using supervised learning. Since Japanese syntactic analysis is usually done after bunsetsu identification, bunsetsu id…

cs.CL1999

An Example-Based Approach to Japanese-to-English Translation of Tense, Aspect, and Modality

M. Murata, Q. Ma, K. Uchimoto +1

We have developed a new method for Japanese-to-English translation of tense, aspect, and modality that uses an example-based method. In this method the similarity between input and…