Automatic labeling and digesting for lecture speech utilizing repeated speech by shift CDP

This paper proposes an automatic labeling and digesting method for lecture speech. The method utilizes same sections, such as same words or same phrases that are thought to be important and are repeated in the speech. To extract the same sections, we have proposed a new efficient algorithm, called Shift Continuous DP, because it is an extension of Continuous DP and realizes fast matching between arbitrary sections in two speech data sets frame-synchronously. Shift CDP is extended to extract same sections in single long speech data in this paper. This paper describes ways to apply the algorithm to labeling and digesting for a lecture speech. We conduct some preliminary experiments to show the method can extract same sections and a sequence of extracted sections can be regarded as a digest of the speech.