Automatic dialogue act recognition with syntactic features.
This work studies the usefulness of syntactic information in the context of automatic dialogue act recognition in Czech. Several pieces of evidence are presented in this work that support our claim that syntax might bring valuable information for dialogue act recognition. In particular, a parallel i...
| Publicado en: | Language Resources & Evaluation Vol. 48; no. 3; pp. 419 - 442 |
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| Autores principales: | , |
| Formato: | Artículo |
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Springer Nature
Sep2014
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=97523002&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 97523002 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Sep2014 vid: 48 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 97523002 10.1007/s10579-014-9263-6 ppf: 419 ppct: 23 formats: fmt: @attributes: type: P size: 444KB tig: atl: Automatic dialogue act recognition with syntactic features. aug: au: Král, Pavel Cerisara, Christophe affil: LORIA UMR 7503, 54506 Vandoeuvre France su: Automatic speech recognition Syntax in programming languages Czech language Computational linguistics Computational learning theory sug: subj: Automatic speech recognition Syntax in programming languages Czech language Computational linguistics Computational learning theory keyword: Dialogue act Language model Sentence structure Speech act Speech recognition Syntax ab: This work studies the usefulness of syntactic information in the context of automatic dialogue act recognition in Czech. Several pieces of evidence are presented in this work that support our claim that syntax might bring valuable information for dialogue act recognition. In particular, a parallel is drawn with the related domain of automatic punctuation generation and a set of syntactic features derived from a deep parse tree is further proposed and successfully used in a Czech dialogue act recognition system based on conditional random fields. We finally discuss the possible reasons why so few works have exploited this type of information before and propose future research directions to further progress in this area. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2014. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2014 holdings: @attributes: islocal: N |
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