Extractive summarization of broadcast news

From HLT@INESC-ID

Ricardo Daniel Ribeiro

Date

  • 15:30, November 03, 2006
  • 3rd floor meeting room

Speaker

Abstract

We present early results from our work on extractive summarization of broadcast news. The feature-based summarizer receives as input the automatic transcription of the news, already divided into stories, and produces as output a summary for each story. The main problems dealt with were sentence segmentation and scoring. Since summary evaluation requires hand-made summaries and/or human grading of the produced summaries, it is left as future work.