Evaluating Artistic Voice of Singing Objectivly Using BPNN

Abstract:

In this paper, an objective way to evaluate artistic voice of singing is discussed. The model transforms artistic voice evaluation indicators into qualified data as BP network input and takes fuzzy synthetic evaluation results as output. The authors take F1(the first Formant), F3(the third Formant), vocal range, 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.

• Periodical: Advanced Materials Research (Volumes 546-547)
• Pages: 1240-1244
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.546-547.1240
• Online since: July 2012
• Authors: Xiao Wu Li, Hong Bo Ouyang
• Keywords: Acoustic Parameter, Artistic Voice, BP Neural Network Analysis, Objective Evaluation

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