  This paper introduces an online speaker diarization system that can handle
long-time audio with low latency. We enable Agglomerative Hierarchy Clustering
(AHC) to work in an online fashion by introducing a label matching algorithm.
This algorithm solves the inconsistency between output labels and hidden labels
that are generated each turn. To ensure the low latency in the online setting,
we introduce a variant of AHC, namely chkpt-AHC, to cluster the speakers. In
addition, we propose a speaker embedding graph to exploit a graph-based
re-clustering method, further improving the performance. In the experiment, we
evaluate our systems on both DIHARD3 and VoxConverse datasets. The experimental
results show that our proposed online systems have better performance than our
baseline online system and have comparable performance to our offline systems.
We find out that the framework combining the chkpt-AHC method and the label
matching algorithm works well in the online setting. Moreover, the chkpt-AHC
method greatly reduces the time cost, while the graph-based re-clustering
method helps improve the performance.
