Speech recognition error correction scheme based on divide-and-conquer

This paper introduced a divide-and-conquer speech recognition error correction scheme. Firstly transformed continuous speech recognition problem into sequential,independent,classification tasks using confusion network( CN) . Each of these sub-tasks could be taken as an isolated word recognition problem and specialized support vector machines ( SVMs) were trained and applied to each problem to discriminate the recognized candidates from CN. Proposed a fast codebook transformation based speech vector alignment method to address the problem that variable length speech vector could not be directly acted as the input vector for SVM. Experiment on a mandarin syllable recognition task shows the proposed scheme can improve the recognition accuracy effectively.