000			01702nam a2200253 4500
001			390350
090			_a390350
100			_a20110620d2004 y0pory50 ba
101			_aeng
200			_aAssessing the discriminative power of voice _fPasupathy Naresh Trilok
210			_aWestchester County, NY _cPace University _d2004
215			_a1 CD-ROM _d12 cm
300			_a"Master’s Dissertation - School of Computer Science and Information System - Pace University - Supervised by Dr. Sung-Hyuk Cha, Dr. Charles Tappert".Disponível em: https://support.csis.pace.edu/CSISWeb/docs/MSThesis/TrilokPasupathyNaresh.pdf (acedido em 20 de Junho de 2011). Ficheiro de 1,03 Mb em formato pdf (57 p.).
330			_a"This study establishes the individuality of voice, using the discriminative power of biometric data quantitatively. The task of establishing voice modality to discriminate every person is difficult because there are a large number of classes for the entire population. The paper proposes a methodology that is statistically inferable. A many class problem is transformed into a dichotomy by using distances between measurements of intra and inter-person classes. This establishes a thorough distinction of classes and thereby validates distinct individuality. This model remains statistically inferable even when it does not observe all the classes."
606			_aEXAME À VOZ _9346274
606			_aIDENTIFICAÇÃO DA VOZ _9345486
606			_aTESE _9334284
606			_aESTADOS UNIDOS _9334103
700			_aTRILOK _bPasupathy Naresh _9356575
955			_xOferta