Synthetic News Radio : content filtering and delivery for broadcast audio news
Name
43926333-MIT.pdf
Description
Full printable version
Size
6.28 MB
Format
Adobe PDF
Checksum (MD5)
21e651785ce7b91559f31f2956cd185b
Author(s)
Emnett, Keith Jeffrey, 1973-
Advisor(s)
Christopher M. Schmandt.
Alternative Title
SNR : content filtering and delivery for broadcast audio news
Date Issued
1999
Publisher
Massachusetts Institute of Technology
Abstract
Synthetic News Radio uses automatic speech recognition and clustered text news stories to automatically find story boundaries in an audio news broadcast, and it creates semantic representations that can match stories of similar content through audio-based queries. Current speech recognition technology cannot by itself produce enough information to accurately characterize news audio; therefore, the clustered text stories represent a knowledge base of relevant news topics that the system can use to combine recognition transcripts of short, intonational phrases into larger, complete news stories. Two interface mechanisms, a graphical desktop application and a touch-tone drive phone interface, allow quick and efficient browsing of the new structured news broadcasts. The system creates a personal, synthetic newscast by extracting stories, based on user interests, from multiple hourly newscasts and then reassembling them into a single recording at the end of the day. The system also supports timely delivery of important stories over a LAN or to a wireless audio pager. This thesis describes the design and evaluation of the news segmentation and content matching technology, and evaluates the effectiveness of the interface and delivery mechanisms.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1999.
Includes bibliographical references (p. 58-59).
Subjects
Architecture. Program In Media Arts and Sciences.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
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