In the present work we investigate the performance of a number of traditional and recent speech enhancement algorithms in the adverse non-stationary conditions, which are distinctive for motorcycle on the move. The performance of these algorithms is ranked in terms of the improvement they contribute to the speech recognition rate, when compared to the baseline result, i.e. without speech enhancement. The experimentations on the MoveOn motorcycle speech and noise database suggested that there is no equivalence between the ranking of algorithms based on the human perception of speech quality and the speech recognition performance. The Multi-band spectral subtraction method was observed to lead to the highest speech recognition performance.
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