• Language and Information
• /
• v.18 no.1
• /
• pp.77-97
• /
• 2014

Multilingual machine translation means the machine translation that is for more than two languages. Common transfer means the transfer in which we can reuse the transfer rules among similar languages according to linguistic typology. Therefore, the multilingual machine translation based on common transfer is the multilingual machine translation that can share the transfer rules among languages with similar linguistic typology. This paper describes the linguistic modeling for multilingual machine translation based on common transfer under development. This linguistic modeling consists of the linguistic devices such as 1) multilingual common Part-of-Speech set, 2) multilingual common transfer format, 3) multilingual common transfer chunking, and 4) multilingual common transfer rules based on linguistic typology. Validity of this linguistic modeling for multilingual machine translation is shown in the simulation. The multilingual machine translation system based on common transfer including Korean, English, Chinese, Spanish, and French will be developed till 2018.

• Journal of Multimedia Information System
• /
• v.8 no.4
• /
• pp.221-232
• /
• 2021

One bottleneck of Bengali to Hindi transfer based machine translation system is the translation of suffixes of noun. The appropriate translation of a nominal suffix often depends on the semantic role of the corresponding noun chunk in the sentence. With the availability of a high performance Bengali morphological analyzer and a basic Bengali parser it is possible to identify the role of each noun chunk. This information may be used for building rules for translating the ambiguous nominal suffixes. As there are some similarities between the uses of Bengali and Hindi nominal suffixes we find that the rules may be identified by linguistically analyzing corpus data. In this paper, we identify rules for the ambiguous four Bengali nominal suffixes from corpus data and evaluate their performances. This set of rules is able to resolve a majority of the nominal suffix ambiguities in Bengali to Hindi transfer based machine translation system. Using the rules, we are able to translate 98.17% Bengali nouns correctly which is much better than the baseline ILMT system's accuracy of 62.8%.

• Journal of Korea Society of Industrial Information Systems
• /
• v.9 no.3
• /
• pp.64-70
• /
• 2004

Korean and Japanese have same structure of sentences because they belong to same family of languages. So, The transfer driven machine translation is most efficient to translate each other. This paper introduce a method which creates a transfer dictionary for Token Based Transfer Driven Koran-Japanese Machine Translation(TB-TDMT). If the transfer dictionaries are created well, we get rid of useless effort for traditional parsing by performing shallow parsing. The semi-parser makes the dependency tree which has minimum information needed output generating module. We constructed the transfer dictionaries by using the corpus obtained from ETRI spoken language database. Our system was tested with 900 utterances which are collected from travel planning domain. The success-ratio of our system is $92\%$ on restricted testing environment and $81\%$ on unrestricted testing environment.

• Language and Information
• /
• v.3 no.1
• /
• pp.65-82
• /
• 1999

The interests in Machine Translation(MT) have gotten revitalized lately with the rapid expansion of internet users. MT technology has gone through several different stages of development, but the longest surviving methods usually maintains the following characteristics: the expand ability and flexibility based on proved linguistic formalism, the transfer method of translation, the continued efforts of systematic updates being made into the system. This paper introduces one such system, L&H Korean-English bidirectional MT system. This system uses Lexical-Functional Grammar as its linguistic framework. It also adopts the transfer method of MT and has been around on the market for over 10 years for other language pairs. Currently, the system covers over 10 different languages including Chinese, Japanese and Arabic, in addition to European languages. This paper will review the system in its core and discuss related tools and resources be ing used to enhance the quality of translation.

• Proceedings of the Korean Society for Language and Information Conference
• /
• 2002.02a
• /
• pp.147-156
• /
• 2002

Aligned parallel corpora have proved very useful in many natural language processing tasks, including statistical machine translation and word sense disambiguation. In this paper, we describe an alignment technique for extracting transfer mapping from the parallel corpus. During building our system and data collection, we observe that there are three types of translation approaches can be used. We especially focuses on Traditional Chinese and Simplified Chinese text lexical translation and a method for extracting transfer mappings for machine translation.

• Journal of the Korea Convergence Society
• /
• v.12 no.10
• /
• pp.27-35
• /
• 2021

Automatic post editing is a research field that aims to automatically correct errors in machine translation results. This research is mainly being focus on high resource language pairs, such as English-German. Recent APE studies are mainly adopting transfer learning based research, where pre-training language models, or translation models generated through self-supervised learning methodologies are utilized. While translation based APE model shows superior performance in recent researches, as such researches are conducted on the high resource languages, the same perspective cannot be directly applied to the low resource languages. In this work, we apply two transfer learning strategies to Korean-English APE studies and show that transfer learning with translation model can significantly improves APE performance.

• Journal of Korea Society of Industrial Information Systems
• /
• v.4 no.4
• /
• pp.40-46
• /
• 1999

This paper introduce a Koran-Japanese machine translation system which is a module in the spoken language interpreting system It is implemented based on the TDMT(Transfre Driven Machine Translation). We define a new unit of translation so called TOKEN. The TOKEN-based translation method resolves nonstructural feature in Korean sentences and increases the quaity of translating results. In our system, we get rid of useless effort for traditional parsing by performing semi-parsing. The semi-parser makes the dependency tree which has minimum information needed generating module. We constructed the generation dictionaries by using the corpus obtained from ETRI spoken language database. Our system was tested with 600 utterances which is collected from travel planning domain The success-ratio of our system is 87% on restricted testing environment and 71% on unrestricted testing environment.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.37 no.3
• /
• pp.1-11
• /
• 2000

An example-based machine translation approach is a new paradigm for resolving various problems caused by the rules of conventional rule-based machine translation. But, in pure example-based machine translation, it is very hard to find similar examples matched with input sentences by using reasonable parallel corpus. This problem causes large overheads in the process of sentence generation. This paper proposes new method of English-Korean transfer using both patterns and examples. The patterns are composed of sentence patterns and phrase patterns. Meta parts of the patterns make the example-based machine translation more practical by raising the probability to find similar examples. The use of patterns and examples can reduce the ambiguities in source language analysis and give us a high quality of MT. And experimental results with a test corpus are discussed.

• Journal of KIISE:Software and Applications
• /
• v.37 no.11
• /
• pp.826-836
• /
• 2010

This paper proposes a hybrid machine translation system which integrates SMT, RBMT, and PBMT in serial manner. SMT in our project has been implemented as a Quasi-syntax-based system where monotone search is done, given a preprocessed string of foreign language. Preprocessing includes rule-based reordering, NE recognition, clausal splitting, and attaching pattern translation information at the end of the input text. For lengthy & complex sentences, clausal splitting turned out to generate better translation than normal input.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.4 s.36
• /
• pp.181-189
• /
• 2005

Due to grammatical similarities, even a one-to-one mapping between Korean and Japanese morphemes can usually result in a high quality Korean-to-Japanese machine translation. So most of Korean-to-Japanese machine translation are based on a one-to-one mapping relation. Most of Korean '-hada' verbs, which consist of a noun and '-hada', also correspond to Japanese '-suru' verbs, which consist of a noun and '-suru', so we generally use one-to-one mapping relation between them. However, the applications only by one-to-one mapping may sometimes result in incorrect Japanese correspondences in some cases that Korean 'hada' verbs don't correspond to Japanese 'suru' verbs. In these cases, we need to handle a noun and '-hada' as one translation unit. Therefore, this paper examined the characteristics of Korean '-hada' verb and proposed transfer rules of Korean 'hada' verb, applying for various states of input sentences such as discontinuity due to inserted words between a noun and '-hada', passivization, and modification of '-hada' verb. In an experimental evaluation, the proposed method was very effective for handling '-hada' verb in a Korean-to-Japanese machine translation, showing high quality of translation results.