液晶与显示2018，Vol.33Issue(2)：165-173,9.DOI:10.3788/YJYXS20183302.0165
基于量子粒子群优化广义回归神经网络的语音转换方法
Voice conversion based on quantum particle swarm optimization of generalized regression neural network
摘要
Abstract
In this paper,a new quantum particle swarm optimization algorithm is used to optimize the voice conversion model of generalized regression neural network in order to solve the problem of slow convergence and premature phenomenon in particle swarm optimization.The quantum particle swarm optimization algorithm changes the position vector by changing the quantum bit phase and uses the quantum non-gate to perform the mutation operation.Therefore,we first use the quantum particle swarm to optimize the network to get the best smooth factor parameters,so as to establish spectrum mapping rules.After that,we use the correlation between the spectral parameters and the fundamental frequency parameters to convert the prosodic characteristic fundamental frequency. Then,the STRAIGHT model is used to synthesize the target voice in conjunction with the converted spectral parameters and the fundamental frequency parameters.Finally,we use the subj ective and ob-j ective evaluation methods to evaluate.The experimental results show that the natural and similarity of the proposed method for the transformed voice are improved and the spectral distortion rate is re-duced by 2.1% compared with the traditional particle swarm optimization algorithm.The proposed method has better voice conversion performance than radial basis function neural network,generalized regression neural network and generalized regression neural network optimized by particle swarm opti-mization.关键词
语音转换/量子粒子群/广义回归神经网络/量子比特/光滑因子Key words
voice conversion/quantum particle swarm optimization/generalized regression neural net-work/quantum bite/smooth factor分类
信息技术与安全科学引用本文复制引用
王民,赵渊,刘利,许娟..基于量子粒子群优化广义回归神经网络的语音转换方法[J].液晶与显示,2018,33(2):165-173,9.基金项目
住房城乡建设部科学技术项目计划(No.2016-R2-045) （No.2016-R2-045）
陕西省教育厅专项基金(No.2013JK1081) （No.2013JK1081）
陕西省科学技术研究发展计划项目(No.CXY1122(2)) （No.CXY1122(2）
陕西省自然科学基金青年基金(No.2013JQ8003)Ministry of Housing and Urban-Rural Development Science and Technology Project plan(No.2016-R2-045) （No.2013JQ8003）
Shaanxi Provincial Department of Education special fund(No.2013JK1081) （No.2013JK1081）
Shaanxi Province Science and Technology Research and Development Project(No.CXY1122(2)) （No.CXY1122(2）
Shaanxi Provincial Natural Science Foundation Youth Fund(No.2013JQ8003) （No.2013JQ8003）
