Transforming online class recording into useful information repositories using NLP methods: An Empirical Study
Cosine Similarity; Keyword retrieval; LDA topic modelling; Text Rank; TF.IDF
Most educational institutions have adapted to the mode of online teaching which has resulted in an increase of online video recordings. Learner community can be benefited with the ability to retrieve required information from the online class recordings. In this paper, we propose a methodology for converting video transcript data into useful information repositories for the purpose of retrieving class transcripts relevant to user's information needs. We focus on the online video recording transcript data. We also discuss challenges in transcribing which are crucial to understand preliminary processing. Our dataset consists of transcripts from diverse subject domains deeper experimental insights. We use interactive transcripts obtained from ASR (automatic speech recognition) services and non-interactive human generated transcripts. State-of-the-art methods for keyword retrieval: Latent Dirichlet Topic Modelling (LDA), Term Frequency (TF.IDF) and Text Rank (graph based) are applied on the video transcript data. Further, cosine similarity metric is applied to obtain the similarity measure between the transcript documents and keywords. 2022 IEEE.
Proceedings - 2022 4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022, pp. 589-594.
Institute of Electrical and Electronics Engineers Inc.
Fernandes D., Christ Deemed to Be University, Department of Computer Science, Bangalore, India; Wagh R.S., Christ Deemed to Be University, Department of Computer Science, Bangalore, India