Active learning with semi-automatic annotation for extractive speech summarization

We propose using active learning for extractive speech summarization in order to reduce human effort in generating reference summaries. Active learning chooses a selective set of samples to be labeled. We propose a combination of informativeness and representativeness criteria for selection. We furt...

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Veröffentlicht in:	ACM transactions on speech and language processing 2012-02, Vol.8 (4), p.1-25
Hauptverfasser:	Zhang, Justin Jian, Fung, Pascale
Format:	Artikel
Sprache:	eng
Schlagworte:	Criteria
Online-Zugang:	Volltext
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