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This paper presents a method for generating indexable and browsable keyword metadata from ASR transcripts by leveraging theWeb. Search engine queries are built from an ASR transcript and used to retrieve similar text from the Web. The keyword meta information embedded in those pages for search engines is then ranked
hypothesized by a primary HMM word spotter to try to improve performance by discriminating true keywords from false alarms. This algorithm is evaluated on a keyword spotting task using the Road Rally Database, and performance is shown to improve significantly over that of the primary word spotter. The segmental model is also used
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.