• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International Journal of Electrical and Computer Engineering >Towards an Optimal Speaker Modeling in Speaker Verification Systems using Personalized Background Models
【24h】

Towards an Optimal Speaker Modeling in Speaker Verification Systems using Personalized Background Models

机译：使用个性化背景模型实现说话人验证系统中的最佳说话人建模

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper presents a novel speaker modeling approachfor speaker recognition systems. The basic idea of this approach consists of deriving the target speaker model from a personalized background model, composed only of the UBM Gaussian components which are really present in the speech of the target speaker. The motivation behind the derivation of speakers’ models from personalized background models is to exploit the observeddifference insome acoustic-classes between speakers, in order to improve the performance of speaker recognition systems. The proposed approach was evaluatedfor speaker verification task using various amounts of training and testing speech data. The experimental results showed that the proposed approach is efficientin termsof both verification performance and computational cost during the testing phase of the system, compared to the traditional UBM based speaker recognition systems.
机译：本文提出了一种新颖的说话人识别系统的说话人建模方法。这种方法的基本思想是从个性化背景模型中得出目标讲话者模型，该模型仅由目标讲话者的语音中确实存在的UBM高斯分量组成。从个性化背景模型中导出说话者模型的动机是，利用说话者之间某些声学类别中观察到的差异，以提高说话者识别系统的性能。使用各种数量的训练和测试语音数据对提议的方法进行了评估，以用于说话人验证任务。实验结果表明，与传统的基于UBM的说话人识别系统相比，该方法在系统测试阶段的验证性能和计算成本方面都是有效的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号