Chart-Based Transfer Rule Application in Machine Translation
نویسندگان
چکیده
Transfer-based Machine Translation systems require a procedure for choosing the set of transfer rules for generating a target language translation from a given source language sentence. In an MT system with many competing transfer rules, choosing the best set of transfer rules for translation may involve the evaluation of an explosive number of competing sets. We propose a solution to this problem based on current bestrst chart parsing algorithms.
منابع مشابه
Control Chart Recognition Patterns using Fuzzy Rule-Based System
Control Chart Patterns (CCPs) recognition is one the most important concepts in control chart application. Relating the patterns exhibited on the control chart to assignable causes is an ambiguous and vague task especially when multiple patterns co-exist. In this study, a fuzzy rule-based system is developed for X ̅ control charts to prioritize the control chart causes based on the accumulated e...
متن کاملLattice Parsing to Integrate Speech Recognition and Rule-Based Machine Translation
In this paper, we present a novel approach to integrate speech recognition and rulebased machine translation by lattice parsing. The presented approach is hybrid in two senses. First, it combines structural and statistical methods for language modeling task. Second, it employs a chart parser which utilizes manually created syntax rules in addition to scores obtained after statistical processing...
متن کاملChart-based Incremental Transfer in Machine Translation
The transfer stage of a machine translation system for spontaneously spoken language in any case has to work incrementally and time-synchronously to be acceptable within natural dialogue settings. To achieve some of the necessary properties, we start from data structures and algorithms as known from chart parsing. Techniques used in this framework for analysis can be applied to the transfer sta...
متن کاملA Hybrid Machine Translation System Based on a Monotone Decoder
In this paper, a hybrid Machine Translation (MT) system is proposed by combining the result of a rule-based machine translation (RBMT) system with a statistical approach. The RBMT uses a set of linguistic rules for translation, which leads to better translation results in terms of word ordering and syntactic structure. On the other hand, SMT works better in lexical choice. Therefore, in our sys...
متن کاملA Synchronous Context Free Grammar using Dependency Sequence for Syntax-based Statistical Machine Translation
We introduce a novel translation rule that captures discontinuous, partial constituent, and non-projective phrases from source language. Using the traversal order sequences of the dependency tree, our proposed method 1) extracts the synchronous rules in linear time and 2) combines them efficiently using the CYK chart parsing algorithm. We analytically show the effectiveness of this translation ...
متن کامل