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StreamHover: Livestream Transcript Summarization and Annotation

StreamHover is a framework for annotating and summarizing livestream transcripts. It uses a neural extractive summarization model that leverages vector-quantized variational autoencoder to learn latent vector representations of spoken utterances and identify salient utterances from the transcripts to form summaries.

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Cite this as

Sangwoo Cho, Franck Dernoncourt, Tim Ganter, Trung Bui, Nedim Lipka, Hassan Foroosh, Fei Liu (2024). Dataset: StreamHover: Livestream Transcript Summarization and Annotation. https://doi.org/10.57702/xxvjs6q4

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Additional Info

Field Value
Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.2109.05160
Author Sangwoo Cho
More Authors
Franck Dernoncourt
Tim Ganter
Trung Bui
Nedim Lipka
Hassan Foroosh
Fei Liu
Homepage https://github.com/ucfnlp/streamhover