Title :
Objective Evaluation of Artistic Voice of Singing Based on BPNN
Author :
Wu Xue-jun ; Luo Lan-e ; Wang Xiu-xin
Author_Institution :
Sch. of Phys. & Electron. Eng., Xiangfan Univ., Xiangfan, China
Abstract :
In this paper, an objective way to evaluate artistic voice of singing is discussed. The authors take F1 (the first formant), F3 (the third formant), fundamental frequency, vocal range, perturbation of fundamental frequency, perturbation of F1, perturbation of F3 and average energy as the evaluating parameters and assess the quality of singing voices with BPNN (back propagation neural network). The results are then compared with the subjective evaluation of experienced professionals. Experiments show that BP neural network is effective to evaluate the singing voices, thus to be helpful to scientific guidance of selecting and training the talent of artistic voice.
Keywords :
acoustic signal processing; backpropagation; neural nets; speech processing; BP neural network; acoustic parameter; artistic voice; back propagation neural network; fundamental frequency; singing voice; vocal range; voice quality; Acoustic propagation; Computer science; Electronic mail; Frequency estimation; Genetic engineering; Muscles; Neural networks; Physics computing; Speech analysis; Timbre; BP neural network analysis; acoustic parameter; objective evaluation;
Conference_Titel :
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-0-7695-3899-0
DOI :
10.1109/WGEC.2009.19