  This paper describes the FBK's participation in the Simultaneous Translation
Evaluation Campaign at IWSLT 2024. For this year's submission in the
speech-to-text translation (ST) sub-track, we propose SimulSeamless, which is
realized by combining AlignAtt and SeamlessM4T in its medium configuration. The
SeamlessM4T model is used "off-the-shelf" and its simultaneous inference is
enabled through the adoption of AlignAtt, a SimulST policy based on
cross-attention that can be applied without any retraining or adaptation of the
underlying model for the simultaneous task. We participated in all the Shared
Task languages (English->{German, Japanese, Chinese}, and Czech->English),
achieving acceptable or even better results compared to last year's
submissions. SimulSeamless, covering more than 143 source languages and 200
target languages, is released at: https://github.com/hlt-mt/FBK-fairseq/.
