This paper proposes a method to resolve the reference of deictic Japanese zero pronouns which can be implemented in a practical machine translation system. This method focuses on semantic and pragmatic constraints such as semantic constraints on cases, modal expressions, verbal semantic attributes and conjunctions to determine the deictic reference of Japanese zero pronouns. This method is highly effective because the volume of knowledge that must be prepared beforehand is not very large and its precision of resolution is good. This method was implemented in the Japanese-to-English machine translation system, ALT-J/E. According to a window test for 175 zero pronouns with deictic referent in a sentence set for the evaluation of Japaneseto-English machine translation systems, all of zero pronouns could be resolved consistently and correctly.
This paper addresses the challenging problem of automatically evaluating output from machine translation (MT) systems in order to support the developers of these systems. Conventional approaches to the problem include methods that automatically assign a rank such as A, B, C, or D to MT output according to a single edit distance between this output and a correct translation example. The single edit distance can be differently designed, but changing its design makes assigning a certain rank more accurate, but another rank less accurate. This inhibits improving accuracy of rank assignment. To overcome this obstacle, this paper proposes an automatic ranking method that, by using multiple edit distances, encodes machine-translated sentences with a rank assigned by humans into multi-dimensional vectors from which a classifier of ranks is learned in the form of a decision tree (DT). The proposed method assigns a rank to MT output through the learned DT. The proposed method is evaluated using transcribed texts of real conversations in the travel arrangement domain. Experimental results show that the proposed method is more accurate than the single-edit-distance-based ranking methods, in both closed and open tests. Moreover, the proposed method could estimate MT quality within 3% error in some cases.
This paper proposes a method to resolve intrasentential references of Japanese zero pronouns suitable for application in widely used and practical machine translation systems. This method focuses on semantic and pragmatic constraints such as conjunctions, verbal semantic attributes and modal expressions to determine intrasentential antecedents of Japanese zero pronouns. This method is highly effective because the volume of knowledge that must be prepared beforehand is not so large and its precision of resolution is good. This method was realized in Japanese to English machine translation system, ALT-J/E. To evaluate the performance of our method, we conducted a windowed test for 139 zero pronouns with intrasentential antecedents in a sentence set for the evaluation of the performance of Japanese to English machine translation systems (3718 sentences). According to the evaluation, intrasentential antecedents could be resolved correctly for 98% of the zero pronouns examined using rules consistent for intersentential and extrasentential resolution. The accuracy was higher than the accuracy of the centering algorithm which is a conventional method to resolve zero pronouns. By the further examination of the evaluation, we found that this method can achieve high accuracy using relatively simple rules.
A method of anaphoral resolution of zero pronouns in Japanese language texts using the verbal semantic attributes is suggested. This method focuses attention on the semantic attributes of verbs and examines the context from the relationship between the semantic attributes of verbs governing zero pronouns and the semantic attributes of verbs governing their referents. The semantic attributes of verbs are created using 2 different viewpoints: dynamic characteristics of verbs and the relationship of verbs to cases. By using this method, it is shown that, in the case of translating newspaper articles, the major portion (93%) of anaphoral resolution of zero pronouns necessary for machine translation can be achieved by using only linguistic knowledge. Factors to be given special attention when incorporating this method into a machine translation system are examined, together with suggested conditions for the detection of zero pronouns and methods for their conversion. This study considers four factors that are important when implementing this method in a Japanese to English machine translation system: the difference in conception between Japanese and English expressions, the difference in case frame patterns between Japanese and English, restrictions by voice and restriction by translation structure. Implementation of the proposed method with due consideration of these points leads to a viable method for anaphoral resolution of zero pronouns in a practical machine translation system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.