  Simultaneous speech translation (SimulST) is a demanding task that involves
generating translations in real-time while continuously processing speech
input. This paper offers a comprehensive overview of the recent developments in
SimulST research, focusing on four major challenges. Firstly, the complexities
associated with processing lengthy and continuous speech streams pose
significant hurdles. Secondly, satisfying real-time requirements presents
inherent difficulties due to the need for immediate translation output.
Thirdly, striking a balance between translation quality and latency constraints
remains a critical challenge. Finally, the scarcity of annotated data adds
another layer of complexity to the task. Through our exploration of these
challenges and the proposed solutions, we aim to provide valuable insights into
the current landscape of SimulST research and suggest promising directions for
future exploration.
