Wordy: Interactive Word Cloud to Summarize and Browse Online Videos to Enhance eLearning

Zhu, Weiwei; Zang, Jun; Tobita, Hiroaki

doi:10.1109/sii46433.2020.9026306

Cited by 6 publications

(2 citation statements)

References 15 publications

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“…using genetic algorithms) to identify the temporal splits that optimize one or multiple objective functions [38], [40]. Other usage of audio transcripts of lecture videos include summaries based on word clouds with support for advanced key-word based navigation [42], abstractive textual lecture video summaries [43], generation of mappings between lecture video segments and text book sub-sections [41] and semantic annotation of lecture videos for recommender systems [44]. None of the lecture video summarization methods evaluated in this work use audio signals or transcripts.…”

Section: ) Audio-based Analysismentioning

confidence: 99%

FCN-LectureNet: Extractive Summarization of Whiteboard and Chalkboard Lecture Videos

Davila

Setlur

et al. 2021

IEEE Access

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Recording and sharing of educational or lecture videos has increased in recent years. Within these recordings, we find a large number of math-oriented lectures and tutorials which attract students of all levels. Many of the topics covered by these recordings are better explained using handwritten content on whiteboards or chalkboards. Hence, we find large numbers of lecture videos that feature the instructor writing on a surface. In this work, we propose a novel method for extraction and summarization of the handwritten content found in such videos. Our method is based on a fully convolutional network, FCN-LectureNet, which can extract the handwritten content from the video as binary images. These are further analyzed to identify the unique and stable units of content to produce a spatial-temporal index of handwritten content. A signal which approximates content deletion events is then built using information from the spatial-temporal index. The peaks of this signal are used to create temporal segments of the lecture based on the notion that sub-topics change when large portions of content are deleted. Finally, we use these segments to create an extractive summary of the handwritten content based on key-frames. This will facilitate content-based search and retrieval of these lecture videos. In this work, we also extend the AccessMath dataset to create a novel dataset for benchmarking of lecture video summarization called LectureMath. Our experiments on both datasets show that our novel method can outperform existing methods especially on the larger and more challenging dataset. Our code and data will be made publicly available.INDEX TERMS fully convolutional networks, handwritten text detection, image binarization, lecture videos, video summarization.

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Section: ) Audio-based Analysismentioning

confidence: 99%

FCN-LectureNet: Extractive Summarization of Whiteboard and Chalkboard Lecture Videos

Davila

Setlur

et al. 2021

IEEE Access

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“…However, these systems do not help to make decision of the discussion. "Wordy," which creates a word cloud based on lecture video content, allows a user to find the points they want to see in the video [14]. "Discussion Mining" generates structured data on discussion content semi-automatically and displays a graph structuralized with the pertinent information and keyword [15].…”

Section: Introductionmentioning

confidence: 99%

A Facilitator Support System that Overlooks Keywords Expressing the True Intentions of All Discussion Participants

Oshima¹,

Oyama²,

Sasaki³

et al. 2021

IJACSA

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This paper proposed the Keyword Movement Disclose System (KMDS), which allows a facilitator of discussion to watch a record of the moving keywords in a Discussion Board System (DBS). In the DBS, the discussion participants place each keyword in a box made for each item to be discussed. The keywords in the box were expected to show each participant's opinion and intention, because the participant's individual display was not disclosed to the other participants. Therefore, if the facilitator of the discussion can see the true opinions and intentions of all participants via the keywords in the boxes through the KMDS, the facilitator will be more appropriately advance the discussions and be able to draw conclusions based on diverse opinions. Moreover, the KMDS may contribute to the development of an artificial intelligence facilitator. In this paper, we conducted an experiment in which ten facilitators were asked to listen to a recorded discussion held by nine participants using the DBS. Five of the facilitators used the KMDS while listening the recorded discussion. It was suggested that KMDS may allow the facilitators to build a consensus from various viewpoints of the participants, although the results of the experiment did not show much difference depending on the conditions with/without KMDS.

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E-learning: A Temporary ‘By-Product’ of Covid-19 Pandemic or a Contemporary Solution to Workplace Training and Learning?

Mitsakis

Karageorgakis²

2020

The Future of HRD, Volume I

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Undoubtedly, we live in an era of global social, business and economic uncertainty due to the Covid-19 outbreak. The sudden lockdown of many businesses and educational institutions necessitated the need for e-learning more than ever before. E-learning represents the safest way to train in times of global crisis as it allows the trainers and the trainees to virtually interact through an online platform which serves as the e-classroom, free of the dangers entailed by physical interaction. Yet, the extent to which this sudden shift to online learning represents the future of workplace training and learning or whether it is just a temporary alteration for human resource development is debatable. The Covid-19 pandemic is expected to accelerate learning and work reinvention, resulting in multiple implications for businesses in relation to institutional resilience. Humankind could learn from its history to fight the pandemic while human resource development (HRD) professionals could reflect on previous uncertain times to inform their current practices.

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Wordy: Interactive Word Cloud to Summarize and Browse Online Videos to Enhance eLearning

Cited by 6 publications

References 15 publications

FCN-LectureNet: Extractive Summarization of Whiteboard and Chalkboard Lecture Videos

FCN-LectureNet: Extractive Summarization of Whiteboard and Chalkboard Lecture Videos

A Facilitator Support System that Overlooks Keywords Expressing the True Intentions of All Discussion Participants

E-learning: A Temporary ‘By-Product’ of Covid-19 Pandemic or a Contemporary Solution to Workplace Training and Learning?

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