Multimodal summarization of meeting recordings

Erol, Berna; Lee, D.-S.; Hull, Jonathan J.

doi:10.1109/icme.2003.1221239

Cited by 43 publications

(32 citation statements)

References 9 publications

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“…A related area of research is the automatic generation of (multimodal) summaries of a meeting (see e.g. [17]). In fact, a summary can be seen as an answer to a question, where the best summary is perhaps the one that answers the most frequently asked questions.…”

Section: Assistance After the Meetingmentioning

confidence: 99%

Pro-active meeting assistants: attention please!

Rienks

Nijholt

Barthelmess³

2007

AI & Soc

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This paper gives an overview of pro-active meeting assistants, what they are and when they can be useful. We explain how to develop such assistants with respect to requirement definitions and elaborate on a set of Wizard of Oz experiments, aiming to find out in which form a meeting assistant should operate to be accepted by participants and whether the meeting effectiveness and efficiency can be improved by an assistant at all.

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Section: Assistance After the Meetingmentioning

confidence: 99%

Pro-active meeting assistants: attention please!

Rienks

Nijholt

Barthelmess³

2007

AI & Soc

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“…Erol et al (2003) aim to create important segments of a meeting recording based on audio, text and visual activity analysis. Tjondronegoro et al (2011) propose a way to summarize a sporting event by analyzing the textual information extracted from multiple resources and identifying the important content in a sport video.…”

Section: Multi-modal Summarizationmentioning

confidence: 99%

“…The existing applications related to MMS include meeting record summarization (Erol et al, 2003;Gross et al, 2000), sport video summarization (Tjondronegoro et al, 2011;Hasan et al, 2013), movie summarization (Evangelopoulos et al, 2013;Mademlis et al, 2016), pictorial storyline summarization (Wang et al, 2012), timeline summarization (Wang et al, 2016b) and social multimedia summarization (Del Fabro et al, 2012;Bian et al, 2013;Schinas et al, 2015;Bian et al, 2015;Shah et al, 2015Shah et al, , 2016. When summarizing meeting recordings, sport videos and movies, such videos consist of synchronized voice, visual and captions.…”

Section: Introductionmentioning

confidence: 99%

Multi-modal Summarization for Asynchronous Collection of Text, Image, Audio and Video

Li¹,

Zhu²,

Ma³

et al. 2017

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

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The rapid increase in multimedia data transmission over the Internet necessitates the multi-modal summarization (MMS) from collections of text, image, audio and video. In this work, we propose an extractive multi-modal summarization method that can automatically generate a textual summary given a set of documents, images, audios and videos related to a specific topic. The key idea is to bridge the semantic gaps between multi-modal content. For audio information, we design an approach to selectively use its transcription. For visual information, we learn the joint representations of text and images using a neural network. Finally, all of the multimodal aspects are considered to generate the textual summary by maximizing the salience, non-redundancy, readability and coverage through the budgeted optimization of submodular functions. We further introduce an MMS corpus in English and Chinese, which is released to the public 1 . The experimental results obtained on this dataset demonstrate that our method outperforms other competitive baseline methods.

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“…One method for creating summaries for recorded meetings is described in [2]. We employ similar algorithms in realtime in an on-going session to create the history directly.…”

Section: Related Workmentioning

confidence: 99%

“…Tools that create summaries of recorded sessions or video are also common [2][4], but while these tools can make it much easier to get a quick overview of a session they still need a complete recording of the session. The history tool described in this paper only store a minimum of information needed; the summaries are created at real time during the session and stored in a database for easy and flexible access to information.…”

Section: Introductionmentioning

confidence: 99%