The popularity of podcasts and online audio is growing by leaps and bounds. In fact, 7.7 million people will be listening to podcasts weekly by 2010, versus an estimated 1.5 million listeners in 2006, according to Bridge Ratings, a provider of radio-audience trend information. With an increase in the quantity of available audio content, however, comes the question of how to find relevant content within audio files.
To address this, a few companies have developed a technology that applies spoken-word search techniques to audio content, as well as to the audio portion of video files. TVEyes' Podscope search engine, for instance, ferrets out audio content on the Web, then uses speech-recognition algorithms on that content, generating an index that can be searched by consumers and business users alike.
Although the use of spoken-word search is bound to make inroads into the consumer space first, it holds potential for use in the enterprise as well, just as instant messaging, blogging and wikis have. Although three big search vendors, Google, MSN and Yahoo, have yet to take outwardly visible action surrounding spoken-word technology, AOL has partnered with TVEyes, and launched a beta of TVEyes' search engine on its site this summer. We expect momentum around spoken-word search to continue to build, whether based on TVEyes' technology or a competing one.