  The paper describes the BUT Automatic Speech Recognition (ASR) systems
submitted for OpenSAT evaluations under two domain categories such as low
resourced languages and public safety communications. The first was challenging
due to lack of training data, therefore various architectures and multilingual
approaches were employed. The combination led to superior performance. The
second domain was challenging due to recording in extreme conditions such as
specific channel, speaker under stress and high levels of noise. Data
augmentation process was inevitable to get reasonably good performance.
