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PodZinger Intros Speech Recognition Based Podcast Search

January 13, 2006

podzinger.gifPodZinger has officially launched its podcast search engine, which uses speech-to-text conversion to help index podcasts.

According to PodZinger, the service has two unique features: it displays the text surrounding the search term, so users can skim results the same way they skim text search results to assess relevance quickly; and it allows users to listen to the most relevant sections of their search results by simply clicking on any word in the search result and beginning audio playback from there.

"At PodZinger, we've used three decades of speech recognition research and development to enable users to search multimedia content as easily as they search text," said Alex Laats, president, Delta Division, BBN Technologies. "PodZinger delivers both visual and audio cues for users to gauge relevance in seconds, eliminating the need to listen to an entire segment to find the right nugget of information."

PodZinger uses speech-to-text technology to create a text index of the audio, which enables users to find content within podcasts and jump directly to the point where their keyword is spoken. From the PodZinger site, users can subscribe to podcasts, download or listen to them, and have PodZinger automatically deliver new podcasts on their topics of interest using RSS feeds.

PodZinger joins PodScope and other services that index podcasts using speech to text conversion.

Source: PodZinger

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