AMIC: Affective multimedia analytics with inclusive and natural communication
Resumen: Traditionally, textual content has been the main source of information extraction and indexing, and other technologies that are capable of extracting information from the audio and video of multimedia documents have joined later. Other major axis of analysis is the emotional and affective aspect intrinsic in human communication. This information of emotions, stances, preferences, figurative language, irony, sarcasm, etc. is fundamental and irreplaceable for a complete understanding of the content in conversations, speeches, debates, discussions, etc. The objective of this project is focused on advancing, developing and improving speech and language technologies as well as image and video technologies in the analysis of multimedia content adding to this analysis the extraction of affective-emotional information. As additional steps forward, we will advance in the methodologies and ways for presenting the information to the user, working on technologies for language simplification, automatic reports and summary generation, emotional speech synthesis and natural and inclusive interaction.
Idioma: Inglés
DOI: 10.26342/2018-61-19
Año: 2018
Publicado en: PROCESAMIENTO DEL LENGUAJE NATURAL 61 (2018), 147-150
ISSN: 1135-5948

Factor impacto SCIMAGO: 0.235 - Computer Science Applications (Q2) - Linguistics and Language (Q2) - Language and Linguistics (Q2)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2017-85854-C4-1-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2017-85854-C4-2-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2017-85854-C4-3-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2017-85854-C4-4-R
Tipo y forma: Article (Published version)
Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes.


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