• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2014, Vol. 36 ›› Issue (01): 39-43.

• 论文 • 上一篇    下一篇

基于量子模距离的说话人识别方法

罗辉,潘平,王洋   

  1. (贵州大学计算机科学与信息学院,贵州 贵阳 550025)
  • 收稿日期:2013-01-07 修回日期:2013-04-10 出版日期:2014-01-25 发布日期:2014-01-25
  • 基金资助:

    贵州省科学技术基金项目(黔科合J字[2012]2132);贵阳市科技计划项目(筑科合同[2011101]1-2号)

Speaker recognition method based on quantum model distance      

LUO Hui,PAN Ping,WANG Yang   

  1. (College of Computer Science and Information,Guizhou University,Guiyang 550025,China)
  • Received:2013-01-07 Revised:2013-04-10 Online:2014-01-25 Published:2014-01-25

摘要:

概率测度和距离测度是模式识别最基本的两种测度,矢量量化算法是典型的基于距离测度的模式识别算法。根据量子模距离测度理论,在矢量量化算法的基础上,探索一种基于量子模距离的说话人识别方法。该方法针对说话人语音的时变性、随机性、特征维数较高等特点,将一帧语音信号视为一个量子态,并根据量子测量理论,对量子态之间进行模距离测量,从而对量子态进行有效的分类和聚类。研究表明该方法能有效地降低语音信号处理的复杂度。在经典计算机上的仿真表明,该方法在运行时间上略优于矢量量化算法,在识别率上明显优于矢量量化算法,为说话人识别的理论研究提供了新的途径。

关键词: 量子, 模距离, 说话人, 识别

Abstract:

Probability measure and distance measure are the most basic measures in pattern recognition, and vector quantization is a typical pattern recognition algorithm based on distance measure. According to the theory of quantum model distance measure, on the basis of vector quantization method, the paper explores a speaker recognition method based on quantum model distance. In order to deal with the timevarying property, the randomness and the highdimensional characteristics of speaker’s voice, we see a frame of speech signal as a quantum state, and measure model distance between quantum states according to quantum measurement theory. Simulation results in classical computer demonstrate that this method has slightly better in terms of operating time and visibly better in terms of recognition rate than vector quantization. It can provide a new way for the theoretical investigation on speaker recognition.

Key words: quantum;model distance;speaker;recognition