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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.

This paper addressees the problem of eliminating unsatisfactory outputs from machine translation (MT) systems. The authors intend to eliminate unsatisfactory MT outputs by using confidence measures. Confidence measures for MT outputs include the rank-sum-based confidence measure (RSCM) for statistical machine translation (SMT) systems. RSCM can be applied to non-SMT systems but does not always work well on them. This paper proposes an alternative RSCM that adopts a mixture of the N-best lists from multiple MT systems instead of a single-system's N-best list in the existing RSCM. In most cases, the proposed RSCM proved to work better than the existing RSCM on two non-SMT systems and to work as well as the existing RSCM on an SMT system. * This research was supported in part by the Ministry of Public Management, Home Affairs, Posts and Telecommunications, Japan. 1 These confidence measures are a kind of automatic evaluator such as mWER (Niessen et al., 2000) and BLEU (Papineni et al., 2001). While mWER and BLEU cannot be used online, these confidence measures can. This is because the former are based on reference translations, while the latter is not.

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This paper proposes a system of 97 verbal semantic attributes for Japanese verbs which considers both dynamic characteristics and the relationship of verbs to cases. These attribute values are used to disambiguate the meanings of all Japanese and English pattern pairs in a Japanese to English transfer pattern dictionary consisting of 15,000 pairs of Japanese valence patterns and equivalent English syntactic structures.