MANDARIN SINGING VOICE SYNTHESIS USING ANN VIBRATO PARAMETER MODELS

摘要：

In this paper, the vibrato parameters of sung syllables are analyzed by using short-time Fourier transform and the method of analytic signal. After the vibrato parameter values for all training syllables are obtained, they are used to train an artificial neural network (ANN) for each type of vibrato parameter. Then, these ANN models are used to generate the values of vibrato parameters. Next, these parameter values and other music information are used together to control a harmonic-plus-noise (IINM) model to synthesize singing voice signals. With the synthetic singing voice, subjective perception tests are conducted. The result show that the singing voice synthesized with the ANN generated vibrato parameters is apparently more natural than the singing voice synthesized with fixed vibrato parameters.

关键词： Singing voice signal synthesis vibrato parameter artificial neural network harmonic-plus-noise model

作者: HUNG-YAN GU ZHENG-FU LIN

作者单位: Department of Computer Science and Information Engineering, Taipei, Taiwan National Taiwan University of Science and Technology, Taipei, Taiwan

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 3288-3293

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）