Tracking of multiple moving sound sources using particle filter for arbitrary microphone array configurations

This study proposes a method to track multiple moving sources based on time-frequency analysis. Specific feature of moving source tracking problem is to obtain accurate estimate provided the speakers are stationary within a short time interval, thus stable estimation would be difficult. At first, basic theory for direction finding is developed for arbitrary array configuration and kernel density estimator approach is applied for tracking multiple simultaneously uttered speeches. Expectation maximization approach for the kernel density estimator and new concept of particle groups corresponding to individual sources are proposed. The method alters the number of particle groups dynamically and it can track multiple source DOAs using short period observation. Through conducted experiments, the method is proved to be effective in real environments.