Retrieving radio news broadcasts in Danish: accuracy and categorization of unrecognized words
Pages 160 - 164
Abstract
Digital archives of radio news broadcasts can possibly be made searchable by combining speech recognition with information retrieval. We explore this possibility for the retrieval of news broadcasts in Danish. An average of 84% of the words in the broadcasts was recognized. Most of the unrecognized words were compounds, names, and other words that appear of value to retrieval. Thus, the set of words describing a broadcast has to be expanded to compensate for the recognition errors. We discuss doing this by exploiting the alternative matches from the speech recognizer and by extracting words from a related corpus.
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- Retrieving radio news broadcasts in Danish: accuracy and categorization of unrecognized words
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Published In
November 2016
706 pages
ISBN:9781450346184
DOI:10.1145/3010915
- Conference Chairs:
- Henry Duh,
- Christopher Lueg,
- Program Chairs:
- Mark Billinghust,
- Weidong Huang
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Publication History
Published: 29 November 2016
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- Innovation Fund Denmark
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OzCHI '16
Sponsor:
- IEEE-SMCS
- Australian Comp Soc
- Data61
- ICACHI
- Infoxchange
- HITLab AU
- James Boag
- Tourism Tasmania
- HFESA
- IEEEVIC
- UTAS
OzCHI '16: The 28th Australian Conference on Human-Computer Interaction
November 29 - December 2, 2016
Tasmania, Launceston, Australia
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