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If you’re using podcasts to get your message to prospective customers, you should know about a whole new way for people to find your content. A new podcast search engine offers a breakthrough that may make podcasts easier to find than ever.


Up until now, podcast search was no better than image search, which depends on searchers using the words around the image file, or the name of the file itself. The search engine does not know that it’s a picture of a zebra—it is counting on the image being named “zebra.gif” (for example). Podcasts, until now, were similarly second-class content, compared to first class Web pages (and blog entries) that can be found by entering any word found on that page.
A new search engine, PODZINGER, takes a new approach, using speech recognition technology to convert podcasts (or any audio) to text. Speech recognition software can “listen” to audio and identify most of the words spoken, converting it to plain computer text, the same as any Web page. Once converted, any text search engine can find that audio file based on any word spoken.
PODZINGER is a neat tool that can help you find podcasts, but search marketers are waiting for mainstream search engines to offer speech recognition—when Google and Yahoo! can perform this trick, the average searcher will start to find podcasts. The development will cause a huge increase in podcast usage. You may even see it happen this year.

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Mike Moran

About Mike Moran

Mike Moran has a unique blend of marketing and technology skills that he applies to raise return on investment for large marketing programs. Mike is a former IBM Distinguished Engineer and a senior strategist at Converseon, a leading social consultancy. Mike is the author of two books on digital marketing, an instructor at several leading universities, as well as a Senior Fellow at the Society for New Communications Research.

4 replies to this post
  1. I tried Pzinger. It was clever; I’m not sure if there is anything else out there that does what it does. podscope is an AV search engine but not focused on podcasts. An observation – the transcription snippits appears to be 50% accurate. Do you think this is acceptable and do you think a full transcription is necessary?

  2. Acceptable is in the eye of the beholder–what I think is important is that we are moving from having no ability to find audio using its contents to suddenly having some ability. I think that makes a world of difference and I think that Yahoo! and Google will be doing it soon. Granted, there are inaccuracies, but I think going from a black box to a gray box is significant progress, even though we all wait for the white box.

  3. I know David Nahamoo and he is very well-respected. It is undoubtedly the case that better speech recognition technology will improve any application, inluding search. I think that the IBM technology would definitely have a big impact on quality when it is applied to search and also believe that even the quality available today has value.

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