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Emotion Detection from Speech and Text
dc.contributor.author | De Velasco Vázquez, Mikel | |
dc.contributor.author | Justo Blanco, Raquel | |
dc.contributor.author | Antón, Josu | |
dc.contributor.author | Carrilero, Mikel | |
dc.contributor.author | Torres Barañano, María Inés | |
dc.date.accessioned | 2019-09-02T14:18:00Z | |
dc.date.available | 2019-09-02T14:18:00Z | |
dc.date.issued | 2018-11-21 | |
dc.identifier.citation | IberSPEECH 2018 21-23 November 2018, Barcelona, Spain : 68-71 (2018) | es_ES |
dc.identifier.uri | http://hdl.handle.net/10810/35128 | |
dc.description.abstract | The main goal of this work is to carry out automatic emo-tion detection from speech by using both acoustic and textualinformation. For doing that a set of audios were extracted froma TV show were different guests discuss about topics of currentinterest. The selected audios were transcribed and annotatedin terms of emotional status using a crowdsourcing platform.A 3-dimensional model was used to define an specific emo-tional status in order to pick up the nuances in what the speakeris expressing instead of being restricted to a predefined set ofdiscrete categories. Different sets of acoustic parameters wereconsidered to obtain the input vectors for a neural network. Torepresent each sequence of words, a models based on word em-beddings was used. Different deep learning architectures weretested providing promising results, although having a corpus ofa limited size. | es_ES |
dc.description.sponsorship | This work has been partially founded by bythe Spanish Government (TIN2014-54288-C4-4-R and TIN2017-85854-C4-3-R), and bythe European Commission H2020 SC1-PM15program under RIA 7 grant 69872. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | International Speech Communication Association | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/769872 | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/TIN2014-54288-C4-4-R | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/TIN2017-85854-C4-3-R | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | emotion detection | es_ES |
dc.subject | speech | es_ES |
dc.subject | text transcriptions | es_ES |
dc.title | Emotion Detection from Speech and Text | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.holder | (c) 2018 ISCA | es_ES |
dc.relation.publisherversion | https://www.isca-speech.org/archive/IberSPEECH_2018/pdfs/IberS18_P1-11_de-Velasco.pdf | es_ES |
dc.identifier.doi | 10.21437/IberSPEECH.2018 | |
dc.contributor.funder | European Commission | |
dc.departamentoes | Electricidad y electrónica | es_ES |
dc.departamentoeu | Elektrizitatea eta elektronika | es_ES |
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