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Investigating an Automatic Method in Summarizing a Video Speech Using User-Assigned Tags

  • Journal of the Korean Society for Library and Information Science
  • 2012, 46(1), pp.163-181
  • DOI : 10.4275/KSLIS.2012.46.1.163
  • Publisher : 한국문헌정보학회
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : January 16, 2012
  • Accepted : February 8, 2012

Kim, Hyun Hee 1

1명지대학교

Accredited

ABSTRACT

We investigated how useful video tags were in summarizing video speech and how valuable positional information was for speech summarization. Furthermore, we examined the similarity among sentences selected for a speech summary to reduce its redundancy. Based on such analysis results, we then designed and evaluated a method for automatically summarizing speech transcripts using a modified Maximum Marginal Relevance model. This model did not only reduce redundancy but it also enabled the use of social tags, title words, and sentence positional information. Finally, we compared the proposed method to the Extractor system in which key sentences of a video speech were chosen using the frequency and location information of speech content words. Results showed that the precision and recall rates of the proposed method were higher than those of the Extractor system, although there was no significant difference in the recall rates.

Citation status

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This paper was written with support from the National Research Foundation of Korea.