关键词: 声源跟踪, 粒子滤波, 定位函数

Abstract: A hybrid speech source tracking algorithm based on particle filtering is presented to improve tracking accuracy in noisy and reverberant environment. According to the characteristic of the received signal whose Signal-to-Noise Ratio（SNR） changes in a wide range, the measurement of the particle set for every signal frame is computed using a localization function of the Steered Response Power-phase Transform（SRP-PHAT）, and its variance is used to determine the SNR level of the received signal frame in this algorithm. For a high-SNR frame, the particle weight is measured by SRP-PHAT, while, for a low-SNR frame, it is measured by the conventional steered beamformer. Simulation results show that the tracking accuracy of both the proposed algorithm and the traditional algorithm is similar in the condition of high average SNR. When the average SNR is lower than 10 dB, and the reverberation time is more than 200 ms, the tracking error of the proposed algorithm decreases by 20%~30%, compared to the traditional algorithm.

Key words: speech source tracking, particle filter, localization function