A Hybrid Model for Extracting Transliteration Equivalents from Parallel Corpora
Several models for transliteration pair acquisition have been proposed to overcome the out-of-vocabulary problem caused by transliterations. To date, however, there has been little literature regarding a framework that can accommodate several models at the same time. Moreover, there is little concer...
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creator | Oh, Jong-Hoon Choi, Key-Sun Isahara, Hitoshi |
description | Several models for transliteration pair acquisition have been proposed to overcome the out-of-vocabulary problem caused by transliterations. To date, however, there has been little literature regarding a framework that can accommodate several models at the same time. Moreover, there is little concern for validating acquired transliteration pairs using up-to-date corpora, such as web documents. To address these problems, we propose a hybrid model for transliteration pair acquisition. In this paper, we concentrate on a framework for combining several models for transliteration pair acquisition. Experiments showed that our hybrid model was more effective than each individual transliteration pair acquisition model alone. |
doi_str_mv | 10.1007/11846406_15 |
format | Conference Proceeding |
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To date, however, there has been little literature regarding a framework that can accommodate several models at the same time. Moreover, there is little concern for validating acquired transliteration pairs using up-to-date corpora, such as web documents. To address these problems, we propose a hybrid model for transliteration pair acquisition. In this paper, we concentrate on a framework for combining several models for transliteration pair acquisition. Experiments showed that our hybrid model was more effective than each individual transliteration pair acquisition model alone.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540390909</identifier><identifier>ISBN: 3540390901</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 354039091X</identifier><identifier>EISBN: 9783540390916</identifier><identifier>DOI: 10.1007/11846406_15</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; English Word ; Exact sciences and technology ; Foreign Word ; Hybrid Model ; Information systems. Data bases ; Memory organisation. Data processing ; Parallel Corpus ; Recall Rate ; Software ; Speech and sound recognition and synthesis. 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To date, however, there has been little literature regarding a framework that can accommodate several models at the same time. Moreover, there is little concern for validating acquired transliteration pairs using up-to-date corpora, such as web documents. To address these problems, we propose a hybrid model for transliteration pair acquisition. In this paper, we concentrate on a framework for combining several models for transliteration pair acquisition. Experiments showed that our hybrid model was more effective than each individual transliteration pair acquisition model alone.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>English Word</subject><subject>Exact sciences and technology</subject><subject>Foreign Word</subject><subject>Hybrid Model</subject><subject>Information systems. Data bases</subject><subject>Memory organisation. Data processing</subject><subject>Parallel Corpus</subject><subject>Recall Rate</subject><subject>Software</subject><subject>Speech and sound recognition and synthesis. Linguistics</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540390909</isbn><isbn>3540390901</isbn><isbn>354039091X</isbn><isbn>9783540390916</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNpNUDtPwzAYNC-JUjrxB7wwMAT82U4cj1VVKFJRGYrEFn1x7CqQxsEOiP57UhUkbrnhHjodIVfAboExdQeQy0yyrID0iFyIVDKhmYbXYzKCDCARQuoTMtEq_9OYPiUjJhhPtJLinExifGMDBGci5SOymtLFrgx1RZ98ZRvqfKDz7z6g6et2Q9cB29jUvQ3Y176l84_P-gsb2_aRuuC39BkDNs0QnPnQ-YCX5MxhE-3kl8fk5X6-ni2S5erhcTZdJh0H3SdglKwESK5cWZnU5WkJDJGnVpnSVLnQJU8VU6piBpxQTivLlbKOS8sRQYzJ9aG3w2iwccNOU8eiC_UWw64AneU58L3v5uCLg9RubChK799jAazYP1r8e1T8AGkjY0g</recordid><startdate>2006</startdate><enddate>2006</enddate><creator>Oh, Jong-Hoon</creator><creator>Choi, Key-Sun</creator><creator>Isahara, Hitoshi</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2006</creationdate><title>A Hybrid Model for Extracting Transliteration Equivalents from Parallel Corpora</title><author>Oh, Jong-Hoon ; Choi, Key-Sun ; Isahara, Hitoshi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p219t-1c74d31427fbdc5f85b10aa25e7cbcd839b257077d0c1f37f97e277ef24e2aa13</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>English Word</topic><topic>Exact sciences and technology</topic><topic>Foreign Word</topic><topic>Hybrid Model</topic><topic>Information systems. Data bases</topic><topic>Memory organisation. Data processing</topic><topic>Parallel Corpus</topic><topic>Recall Rate</topic><topic>Software</topic><topic>Speech and sound recognition and synthesis. Linguistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Oh, Jong-Hoon</creatorcontrib><creatorcontrib>Choi, Key-Sun</creatorcontrib><creatorcontrib>Isahara, Hitoshi</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Oh, Jong-Hoon</au><au>Choi, Key-Sun</au><au>Isahara, Hitoshi</au><au>Pala, Karel</au><au>Sojka, Petr</au><au>Kopeček, Ivan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A Hybrid Model for Extracting Transliteration Equivalents from Parallel Corpora</atitle><btitle>Lecture notes in computer science</btitle><date>2006</date><risdate>2006</risdate><spage>119</spage><epage>126</epage><pages>119-126</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540390909</isbn><isbn>3540390901</isbn><eisbn>354039091X</eisbn><eisbn>9783540390916</eisbn><abstract>Several models for transliteration pair acquisition have been proposed to overcome the out-of-vocabulary problem caused by transliterations. To date, however, there has been little literature regarding a framework that can accommodate several models at the same time. Moreover, there is little concern for validating acquired transliteration pairs using up-to-date corpora, such as web documents. To address these problems, we propose a hybrid model for transliteration pair acquisition. In this paper, we concentrate on a framework for combining several models for transliteration pair acquisition. Experiments showed that our hybrid model was more effective than each individual transliteration pair acquisition model alone.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/11846406_15</doi><tpages>8</tpages></addata></record> |
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source | Springer Books |
subjects | Applied sciences Artificial intelligence Computer science control theory systems English Word Exact sciences and technology Foreign Word Hybrid Model Information systems. Data bases Memory organisation. Data processing Parallel Corpus Recall Rate Software Speech and sound recognition and synthesis. Linguistics |
title | A Hybrid Model for Extracting Transliteration Equivalents from Parallel Corpora |
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