Distributed multiple speaker tracking based on time delay estimation in microphone array network

Multiple speaker tracking in distributed microphone array (DMA) network is a challenging task. A critical issue for multiple speaker scenarios is to distinguish the ambiguous observation and associate it to the corresponding speaker, especially under reverberant and noisy environments. To address the problem, a distributed multiple speaker tracking method based on time delay estimation in DMA is proposed in this study. Specifically, the time delay estimated by the generalised crosscorrelation function is treated as an observation. In order to distinguish the observation for each speaker, the possible time delays, refer to as candidates, are extracted based on data association technique. Considering the ambient influence, a time delay estimation strategy is designed to calculate the time delay for each speaker from the candidates. Finally, only the reliable time delays in DMA are propagated throughout the whole network by diffusion fusion algorithm and used for updating the speakers' state within the distributed Kalman filter framework. The proposed approach can track multiple speakers successfully in a non-centralised manner under reverberant and noisy environments. Simulation results indicate that, compared with other methods, the proposed method can achieve a smaller root mean square error for multiple speaker tracking, especially in adverse conditions.