  Spoken language translation (SLT) has become very important in an
increasingly globalized world. Machine translation (MT) for automatic speech
recognition (ASR) systems is a major challenge of great interest. This research
investigates that automatic sentence segmentation of speech that is important
for enriching speech recognition output and for aiding downstream language
processing. This article focuses on the automatic sentence segmentation of
speech and improving MT results. We explore the problem of identifying sentence
boundaries in the transcriptions produced by automatic speech recognition
systems in the Polish language. We also experiment with reverse normalization
of the recognized speech samples.
