| Texto completo | |
| Autor(es): |
Paraboni, Ivandre
;
Monteiro, Danielle Sampaio
;
Lan, Alex Gwo Jen
;
Ekstein, K
;
Matousek, V
Número total de Autores: 5
|
| Tipo de documento: | Artigo Científico |
| Fonte: | TEXT, SPEECH, AND DIALOGUE, TSD 2017; v. 10415, p. 9-pg., 2017-01-01. |
| Resumo | |
This paper addresses the issue of how Big Five personality traits may influence the content selection task in Referring Expression generation (REG.) To this end, we build a corpus of referring expressions annotated with personality information, and then use it as the input to a machine learning approach to REG that takes the personality of the target speakers into account. Results show that personality-dependent REG outperforms standard REG algorithms, and that it may be a viable alternative to speaker-dependent approaches that require examples of descriptions produced by every individual under consideration. (AU) | |
| Processo FAPESP: | 16/14223-0 - Tratamento Computacional da Personalidade Humana para Aplicações de Processamento de Língua Natural |
| Beneficiário: | Ivandre Paraboni |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |