  It is widely known that hallucination is a critical issue in Simultaneous
Machine Translation (SiMT) due to the absence of source-side information. While
many efforts have been made to enhance performance for SiMT, few of them
attempt to understand and analyze hallucination in SiMT. Therefore, we conduct
a comprehensive analysis of hallucination in SiMT from two perspectives:
understanding the distribution of hallucination words and the target-side
context usage of them. Intensive experiments demonstrate some valuable findings
and particularly show that it is possible to alleviate hallucination by
decreasing the over usage of target-side information for SiMT.
