DC Field | Value | Language |
---|---|---|
dc.contributor.author | Minwoo Jeong | - |
dc.contributor.author | Lee, GG | - |
dc.date.accessioned | 2016-04-01T02:22:04Z | - |
dc.date.available | 2016-04-01T02:22:04Z | - |
dc.date.created | 2011-03-22 | - |
dc.date.issued | 2008-04 | - |
dc.identifier.issn | 0885-2308 | - |
dc.identifier.other | 2008-OAK-0000022977 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/24998 | - |
dc.description.abstract | Spoken language understanding (SLU) addresses the problem of mapping natural language speech to frame structure encoding of its meaning. The statistical sequential labeling method has been successfully applied to SLU tasks; however, most sequential labeling approaches lack long-distance dependency information handling method. In this paper, we exploit non-local features as an estimate of long-distance dependencies to improve performance of the statistical SLU problem. A method we propose is to use trigger pairs automatically extracted by a feature induction algorithm. We describe a light practical version of the feature inducer for which a simple modification is efficient and successful. We evaluate our method on three SLU tasks and show an improvement of performance over the baseline local model. (C) 2007 Elsevier Ltd. All rights reserved. | - |
dc.description.statementofresponsibility | X | - |
dc.language | English | - |
dc.publisher | ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD | - |
dc.relation.isPartOf | COMPUTER SPEECH AND LANGUAGE | - |
dc.subject | Spoken language understanding | - |
dc.subject | Non-local features | - |
dc.subject | Long-distance dependency | - |
dc.subject | Feature induction | - |
dc.title | Practical Use of Non-local Features for Statistical Spoken Language Understanding. | - |
dc.type | Article | - |
dc.contributor.college | 컴퓨터공학과 | - |
dc.identifier.doi | 10.1016/j.csl.2007.07.001 | - |
dc.author.google | Jeong, M | - |
dc.author.google | Lee, GG | - |
dc.relation.volume | 22 | - |
dc.relation.issue | 2 | - |
dc.relation.startpage | 148 | - |
dc.relation.lastpage | 170 | - |
dc.contributor.id | 10103841 | - |
dc.relation.journal | COMPUTER SPEECH AND LANGUAGE | - |
dc.relation.index | SCI급, SCOPUS 등재논문 | - |
dc.relation.sci | SCI | - |
dc.collections.name | Journal Papers | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | COMPUTER SPEECH AND LANGUAGE, v.22, no.2, pp.148 - 170 | - |
dc.identifier.wosid | 000207632300003 | - |
dc.date.tcdate | 2019-02-01 | - |
dc.citation.endPage | 170 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 148 | - |
dc.citation.title | COMPUTER SPEECH AND LANGUAGE | - |
dc.citation.volume | 22 | - |
dc.contributor.affiliatedAuthor | Lee, GG | - |
dc.identifier.scopusid | 2-s2.0-35548931640 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 8 | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | Spoken language understanding | - |
dc.subject.keywordAuthor | Non-local features | - |
dc.subject.keywordAuthor | Long-distance dependency | - |
dc.subject.keywordAuthor | Feature induction | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
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