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Bi-modal annoyance level detection from speech and text
dc.contributor.author | Justo Blanco, Raquel | |
dc.contributor.author | Irastorza Manso, Jon | |
dc.contributor.author | Pérez, Saioa | |
dc.contributor.author | Torres Barañano, María Inés | |
dc.date.accessioned | 2019-09-02T16:22:29Z | |
dc.date.available | 2019-09-02T16:22:29Z | |
dc.date.issued | 2018-09 | |
dc.identifier.citation | Procesamiento del Lenguaje Natural (61) : 83-89 (2018) | es_ES |
dc.identifier.issn | 1135-5948 | |
dc.identifier.uri | http://hdl.handle.net/10810/35133 | |
dc.description.abstract | The main goal of this work is the identification of emotional hints from speech. Machine learning researchers have analysed sets of acoustic parameters as potential cues for the identification of discrete emotional categories or, alternatively, of the dimensions of emotions. However, the semantic information gathered in the text message associated to its utterance can also provide valuable information that can be helpful for emotion detection. In this work this information is included within the acoustic information leading to a better system performance. Moreover, it is noticeable the use of a corpus that include spontaneous emotions gathered in a realistic environment. It is well known that emotion expression depends not only on cultural factors but also on the individual and on the specific situation. Thus, the conclusions extracted from the present work can be more easily extrapolated to a real system than those obtained from a classical corpus with simulated emotions. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Sociedad Española para el Procesamiento del Lenguaje Natural | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | speech processing | es_ES |
dc.subject | semantic information | es_ES |
dc.subject | emotion detection on speech | es_ES |
dc.subject | annoyance tracking | es_ES |
dc.subject | machine learning | es_ES |
dc.title | Bi-modal annoyance level detection from speech and text | es_ES |
dc.title.alternative | Detección del nivel de enfado mediante un sistema bi-modal basado en habla y texto | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.publisherversion | http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/5647 | es_ES |
dc.identifier.doi | 10.26342/2018-61-9 | |
dc.departamentoes | Electricidad y electrónica | es_ES |
dc.departamentoeu | Elektrizitatea eta elektronika | es_ES |