Spontaneous speech and opinion detection: mining call-centre transcripts.
Opinion mining on conversational telephone speech tackles two challenges: the robustness of speech transcriptions and the relevance of opinion models. The two challenges are critical in an industrial context such as marketing. The paper addresses jointly these two issues by analyzing the influence o...
| Publicado en: | Language Resources & Evaluation Vol. 47; no. 4; pp. 1089 - 1126 |
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| Autores principales: | , , , , , , , , , , , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Dec2013
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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=92720002&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 92720002 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Dec2013 vid: 47 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 92720002 10.1007/s10579-013-9224-5 ppf: 1089 ppct: 37 formats: fmt: @attributes: type: P size: 663KB tig: atl: Spontaneous speech and opinion detection: mining call-centre transcripts. aug: au: Clavel, Chloé Adda, Gilles Cailliau, Frederik Garnier-Rizet, Martine Cavet, Ariane Chapuis, Géraldine Courcinous, Sandrine Danesi, Charlotte Daquo, Anne-Laure Deldossi, Myrtille Guillemin-Lanne, Sylvie Seizou, Marjorie Suignard, Philippe affil: EDF R&D, 1 Avenue du Général de Gaulle, 92141, Clamart, France LIMSI, Université Paris XI, Bât 508, BP 133, 91403, Orsay Cedex, France Sinequa, 12 rue d’Athènes, 75009, Paris, France Vecsys, 3 rue Terre de Feu, 91940, Les Ulis, France Vocapia Research, 3 rue Jean Rostand, Parc Orsay Université, 91400, Orsay, France TEMIS, 207 rue de Bercy, 75012, Paris, France su: Oral communication Call centers Transcription (Linguistics) Sentiment analysis Discourse theory (Communication) Automatic speech recognition sug: subj: Oral communication Call centers Transcription (Linguistics) Sentiment analysis Discourse theory (Communication) Automatic speech recognition keyword: Automatic speech recognition system Business concept detection Call-centre data Disfluency Opinion detection ab: Opinion mining on conversational telephone speech tackles two challenges: the robustness of speech transcriptions and the relevance of opinion models. The two challenges are critical in an industrial context such as marketing. The paper addresses jointly these two issues by analyzing the influence of speech transcription errors on the detection of opinions and business concepts. We present both modules: the speech transcription system, which consists in a successful adaptation of a conversational speech transcription system to call-centre data and the information extraction module, which is based on a semantic modeling of business concepts, opinions and sentiments with complex linguistic rules. Three models of opinions are implemented based on the discourse theory, the appraisal theory and the marketers’ expertise, respectively. The influence of speech recognition errors on the information extraction module is evaluated by comparing its outputs on manual versus automatic transcripts. The F-scores obtained are 0.79 for business concepts detection, 0.74 for opinion detection and 0.67 for the extraction of relations between opinions and their target. This result and the in-depth analysis of the errors show the feasibility of opinion detection based on complex rules on call-centre transcripts. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2013. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2013 holdings: @attributes: islocal: N |
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