Computer-assisted transcription of speech based on confusion network reordering

Large vocabulary automatic speech recognition (ASR) technologies perform well in known and controlled contexts. In less controlled conditions, however, human review is often necessary to check and correct the results of such systems in order to ensure that the output of ASR will be understandable. We propose a method for computer-assisted transcription of speech, based on automatic reordering confusion networks. Our method will be evaluated in terms of KSR (Keystroke Saving Rate) and WSR (Word Stroke Ratio). It allows to significantly reduce the number of actions needed to correct ASR outputs. WSR computed before and after every network reordering shows a gain of about 17.7% (3.4 points).