cROVER: Improving ROVER using automatic error detection

Recognizer Output Voting Error Reduction (ROVER), is a well-known procedure for decoders´ combination aiming at reducing the Word Error Rate (WER) in transcription applications. However, it appears that this technique has reached a plateau in terms of performance. This paper presents a novel approach, cROVER, in order to boost the current ROVER performance, by relying on a contextual analysis to trim erroneous words. Experiments have proven that it is possible to outperform ROVER, despite the high false positive rate of the error detection technique.