In this paper, we use such a sequential alignment as our baseline, which takes a standard dynamic-programming process to find the optimal path on an M-by-N similarity matrix, where M and N denote the number of bullets and utterances in a lecture, respectively.
we chose the path that maps each bullet to an utterance to achieve the highest total bullet-utterance similarity score; this path can be found within a standard O(M N 2 ) time complexity.