Fast approximate matching algorithm for phone-based keyword spotting

Generally, exact matching is widely used for keyword spotting (KWS). Its performance depends heavily on the recognition accuracy. As for phone-based KWS system, the influence of phoneme error rate (PER) on KWS increases as the length of phoneme sequence for the keyword grows. Approximate matching is an alteration to compensate errors in recognition. Compared to exact matching, the calculation cost of approximate matching is extremely larger, limiting its application in KWS systems. In this paper, a fast approximate matching algorithm based on phone confusion network (PCN) is proposed. Given the keyword sequence, only paths with possible minimum edit distance are reserved during detection. Then others with larger edit distance are generated by detected ones. All paths are split into sub-paths during processing, which further reduces calculation cost effectively. Experimental results show that our algorithm is faster significantly than before optimization, with little performance degradation. © 2013 ACADEMY PUBLISHER.