MONTE CARLO EXPLORATION FOR ACTIVE BINAURAL LOCALIZATION

被引：0

作者：

Schymura, Christopher ^{[1
]}

Grajales, Juan Diego Rios ^{[1
]}

Kolossa, Dorothea ^{[1
]}

机构：

[1] Ruhr Univ Bochum, Inst Commun Acoust, Bochum, Germany

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2017年

关键词：

sound source localization; robot audition; active listening; particle filters; Monte Carlo exploration; SOUND SOURCE DISTANCE;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This study introduces a machine hearing system for robot audition, which enables a robotic agent to pro-actively minimize the uncertainty of sound source location estimates through motion. The proposed system is based on an active exploration approach, providing a means to model and predict effects of the agent's future motions on localization uncertainty in a probabilistic manner. Particle filtering is used to estimate the posterior probability density function of the source position from binaural measurements, enabling to jointly assess azimuth and distance of the source. The framework allows to infer and refine a policy to select appropriate actions via a Monte Carlo exploration approach. Experiments in simulated reverberant conditions are conducted, showing that active exploration and the incorporation of distance estimation significantly improve localization performance.

引用

页码：491 / 495

页数：5