Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Pinto-Coelho, L., Braga, D., Dias, Miguel Sales & Garcia-Mateo, C. (2013). On the development of an automatic voice pleasantness classification and intensity estimation system. Computer Speech and Language. 27 (1), 75-88
Exportar Referência (IEEE) 
L. P. Coelho et al.,  "On the development of an automatic voice pleasantness classification and intensity estimation system", in Computer Speech and Language, vol. 27, no. 1, pp. 75-88, 2013
Exportar BibTeX 
@article{coelho2013_1732206226428,
	author = "Pinto-Coelho, L. and Braga, D. and Dias, Miguel Sales and Garcia-Mateo, C.",
	title = "On the development of an automatic voice pleasantness classification and intensity estimation system",
	journal = "Computer Speech and Language",
	year = "2013",
	volume = "27",
	number = "1",
	doi = "10.1016/j.csl.2012.01.006",
	pages = "75-88",
	url = "http://www.sciencedirect.com/science/article/pii/S0885230812000083"
}
Exportar RIS 
TY  - JOUR
TI  - On the development of an automatic voice pleasantness classification and intensity estimation system
T2  - Computer Speech and Language
VL  - 27
IS  - 1
AU  - Pinto-Coelho, L.
AU  - Braga, D.
AU  - Dias, Miguel Sales
AU  - Garcia-Mateo, C.
PY  - 2013
SP  - 75-88
SN  - 0885-2308
DO  - 10.1016/j.csl.2012.01.006
UR  - http://www.sciencedirect.com/science/article/pii/S0885230812000083
AB  - In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1 error rate for voice pleasantness classification and a 15.7 error rate for voice pleasantness intensity estimation. 
ER  -