PodZinger Makes Podcast Searching Fast, Easy and Accurate
|Advanced Speech Recognition Technology Delivers Relevant Search Results for Multimedia Content|
“Relevant and content-rich podcast search is now a reality”
PodZinger today announced the launch of its podcast search engine (www.podzinger.com). Based on 30 years of speech recognition research and development from BBN Technologies, PodZinger is the fastest, easiest, and most reliable way for users to find the information they care about in podcasts. Two unique features of PodZinger make it exceptionally powerful and user-friendly: 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.
PodZinger scours the Web daily, adding new podcasts as they become available at the rate of several thousand per week. As the number and content range of available podcasts rapidly expand (fueled in part by traditional media players who are making their content available as RSS series--Really Simple Syndication--), there is a growing need for an effective search technology that lets users find specific content they care about. PodZinger meets this need by enabling users to search audio by keyword in the same way they are used to finding what they want with current text search engines.
"Relevant and content-rich podcast search is now a reality," said Alex Laats, president, Delta Division, BBN Technologies. "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. 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."
Compatible with most popular Web browsers, PodZinger uses speech-to-text technology to create a text index of the audio, which enables users to find content anywhere within podcasts and jump directly to the point where their keyword is spoken. From the PodZinger site, users can also subscribe to podcasts, download or listen to them, and even have PodZinger automatically deliver new podcasts on their own topics of interest using standard RSS feeds.
Podcasters who have already discovered PodZinger have submitted their podcasts directly to PodZinger for indexing and have placed the PodZinger search box on their sites so their listeners can search their podcasts easily. PodZinger's audio search capabilities also provide a new avenue for advertisers, enabling them to target their advertising in this new medium very precisely based on users' areas of interest.
PodZinger is powered by BBN Technologies, leveraging its 30 years of speech recognition research to transform multimedia content into searchable words. PodZinger opens up a previously untapped source of content via a simple Web search. So when it comes to finding what you want in podcasts... just ZING IT!
About BBN Technologies
BBN Technologies, an advanced technology and research and development firm, is focused on solving some of the world's most pressing problems. From national security, information security, speech recognition and language translation, to integrating disparate systems and networks, BBN has been at the forefront of technological change for over 50 years.
Known for pioneering the development of the ARPANET, the forerunner of the Internet, BBN continues to create advances in Internet and networking technologies through its work on ad hoc networking, the semantic Web, quantum communications, and advanced protocols. Building on its substantial list of firsts, BBN operates the first metro quantum cryptography network, the first real-time foreign broadcast monitoring system, and has developed the world's first stereoscopic digital mammography system. For more information on BBN Technologies, visit www.bbn.com.