In this paper, we discuss a combined system for punctuation generation and speech recognition. This system incorporates prosodic information with acoustic and language model information. Experiments are conducted for both the reference transcriptions and speech recogniser outputs. For the reference transcription case, prosodic information is shown to be more useful than language model information. When these information sources are combined, we can obtain an F-measure of up to 0.7830 for punctuation recognition. A few straightforward modifications of a conventional speech recogniser allow the system to produce punctuation and speech recognition hypotheses simultaneously. The multiple hypotheses are produced by the automatic speech recogniser and are re-scored by prosodic information. When prosodic information is incorporated, the F-measure can be improved by 19% relative. At the same time, small reductions in word error rate are obtained.