Educational video classification by using a transcript to image transform and supervised learning
Chatbri, Houssem, Oliveira, Marlon, McGuinness, Kevin, Little, Suzanne, Kameyama, Keisuke, Kwan, Paul, Sutherland, Alistair and O'Connor, Noel E.
(2017)
Educational video classification by using a transcript to image transform and supervised learning.
In: 7th International Conference on Image Processing Theory, Tools and Applications (IPTA), 28 Nov - 1 Dec 2017, Montreal, Canada.
ISBN 978-1-5386-1842-4
(In Press)
In this work, we present a method for automatic topic classification of educational videos using a speech transcript transform. Our method works as follows: First, speech recognition is used to generate video transcripts. Then, the transcripts are converted into images using a statistical co-occurrence transformation that we designed. Finally, a classifier is used to produce video category labels for a transcript image input. For our classifiers, we report results using a convolutional neural network (CNN) and a principal component analysis (PCA) model.
In order to evaluate our method, we used the Khan Academy on a Stick dataset that contains 2,545 videos, where each video is labeled with one or two of 13 categories. Experiments show that our method is effective and strongly competitive against other supervised learning-based methods.
Item Type:
Conference or Workshop Item (Speech)
Event Type:
Conference
Refereed:
Yes
Additional Information:
Research Centre: Insight Centre for Data Analytics
Uncontrolled Keywords:
Educational video classification; transcript features; convolutional neural networks (CNN); principal component analysis (PCA)