Accession Number:

ADA458632

Title:

Automatic Title Generation for Spoken Broadcast News

Descriptive Note:

Conference paper

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA LANGUAGE TECHNOLOGIES INST

Personal Author(s):

Report Date:

2001-01-01

Pagination or Media Count:

4.0

Abstract:

ABSTRACT In this paper, we implemented a set of title generation methods using training set of 21190 news stories and evaluated them on an independent test corpus of 1006 broadcast news documents, comparing the results over manual transcription to the results over automatically recognized speech. We use both F1 and the average number of correct title words in the correct order as metric. Overall, the results show that title generation for speech recognized news documents is possible at a level approaching the accuracy of titles generated for perfect text transcriptions.

Subject Categories:

  • Cybernetics
  • Radio Communications
  • Voice Communications

Distribution Statement:

APPROVED FOR PUBLIC RELEASE