JOURNAL ARTICLE

Quasi-Monte Carlo Filtering for Speaker Tracking

Hou Dai-wenFuliang YinZhe Chen

Year: 2009 Journal:   ACTA AUTOMATICA SINICA Vol: 35 (7)Pages: 1016-1021   Publisher: Elsevier BV

Abstract

摘要: 提出了一种基于拟蒙特卡洛滤波的说话人跟踪方法. 该方法利用拟蒙特卡洛积分技术优化采样粒子在状态空间的分布特性, 降低了滤波过程中的积分误差, 提高了状态估计精度; 同时, 用均值漂移技术使采样粒子向高似然区域移动, 减少了所需采样粒子的数目, 降低了计算需求. 最后, 将所提方法应用于说话人跟踪系统, 提高了说话人位置的跟踪精度. 仿真实验结果验证了本文方法的有效性. 关键词: 说话人跟踪 / 拟蒙特卡洛滤波 / 粒子滤波 / 均值漂移 / 状态估计

Keywords:
Monte Carlo method Computer science Tracking (education) Speech recognition Quasi-Monte Carlo method Particle filter Markov chain Monte Carlo Hybrid Monte Carlo Artificial intelligence Psychology Mathematics Statistics Kalman filter Pedagogy

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Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Speech and Audio Processing
Physical Sciences →  Computer Science →  Signal Processing
Distributed Sensor Networks and Detection Algorithms
Physical Sciences →  Computer Science →  Computer Networks and Communications

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