Sentence-Level Automatic Lecture Highlighting Based on Acoustic Analysis
Xiaoyin Che, Sheng Luo, Haojin Yang, Christoph Meinel · 2016
In this paper we propose a solution which highlights key sentences in lecture video transcripts based on acoustic analysis. The basic idea is that a good lecturer knows when and where to emphasize when giving a lecture and these emphases can be detected by acoustic features of the speech, such as energy, pitch, speaking rate, etc. The selected key sentences are then specially marked in the lecture subtitle and presented to MOOC learners. An evaluation of both example result analysis and user feedback shows that the proposed lecture highlights are relatively logical and accurate. This form of highlighted lecture transcript is also welcomed by our learners.