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一种基于联合源-滤波器模型优化的语音声门源模型估计方法
  • ISSN号：0372-2112
  • 期刊名称：《电子学报》
  • 时间：0
  • 分类：O424[理学—声学;理学—物理]
  • 作者机构：[1]中科信利语音实验室、中国科学院声学研究所,北京100080, [2]爱尔兰里默瑞克大学电子与计算机工程系,里默瑞克 爱尔兰
  • 相关基金：国家自然科学基金（No.10574140,60535030）;国家973重点基础研究发展规划（No.2004CB318106）
作者： 付强[1], Peter Murphy[2], 颜永红[1]
关键词： 语音产生模型, 源-滤波器, 声门波导数, ARX, 声门波估计, 联合优化, speech production model, source-filter model, glottal flow derivative, ARX, glottal source estimation , joint optimization
中文摘要：

本文论述了一种基于联合源-滤波器分离的稳健声门源模型估计方法.此方法利用LF（Liljencrants-Fant）模型对声门波导数（glottal flow derivative）进行建模,而声道被描述为一个时变的ARX模型.由于联合估计问题是一个多变量非线性优化过程,本文采用了一个两阶段（two-pass）的实现策略来解决这一问题.第一阶段初始化声门源和声道模型,并为其后的联合优化过程提供稳健的初始参数.第二阶段的联合估计则最终决定模型估计的精度,由信任域下降优化算法实现.通过分别对合成和真实语音的实验,表明该方法是一种具有一定精度和较好的稳健性的声门源模型估计算法.

英文摘要：

This paper describes a robust glottal source estimation method based on a joint source-filter separation technique. In this method, the glottal flow derivative is modelled as the Liljencrants-Fant （LF） model and the vocal tract is described as a timevarying ARX model.Since the joint estimation problem is a multi-parameter nonlinear optimization procedure, we separate the optimization procedure into two passes. The first pass initializes the glottal source and vocal tract models providing robust initial parameters to the following joint optimization procedure. The joint estimation determines the accuracy of model estimation, which is implemented with a trust-region descent optimization algorithm. Experiments with synthetic and real voices show the proposed method is a robust glottal source parameter estimation method with a considerable degree of accuracy.

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期刊信息
  • 《电子学报》
  • 中国科技核心期刊
  • 主管单位:中国科学技术协会
  • 主办单位:中国电子学会
  • 主编：郝跃
  • 地址：北京165信箱
  • 邮编：100036
  • 邮箱：new@ejournal.org.cn
  • 电话：010-68279116 68285082
  • 国际标准刊号：ISSN：0372-2112
  • 国内统一刊号：ISSN：11-2087/TN
  • 邮发代号:2-891
  • 获奖情况:
  • 2000年获国家期刊奖,2000年获国家自然科学基金志项基金支持,中国期刊方阵“双高”期刊
  • 国内外数据库收录:
  • 美国化学文摘（网络版）,荷兰文摘与引文数据库,美国工程索引,美国剑桥科学文摘,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）,中国北大核心期刊（2011版）,中国北大核心期刊（2014版）,英国英国皇家化学学会文摘,中国北大核心期刊（2000版）
  • 被引量:57611