A multi-fpga 10x-real-time high-speed search engine for a 5000-word vocabulary speech recognizer
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
Video PowerSearcher: a text-based indexing e-learning system
Proceedings of the 1st International Conference on Intelligent Semantic Web-Services and Applications
Multimedia data mining: state of the art and challenges
Multimedia Tools and Applications
International Journal of Reconfigurable Computing - Special issue on selected papers from the southern programmable logic conference (SPL2010)
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he Web, databases, and other digitized information storehouses contain a growing volume of audio content. Sources include newscasts, sporting events, telephone conversations, recordings of meetings, Webcasts, documentary archives such as the Visual History Foundation's interviews with Holocaust survivors (http://www.vhf. org), and media files in libraries. Users want to make the most of this material by searching and indexing the digitized audio content. In the past, companies had to create and manually analyze written transcripts of audio content because using computers to recognize, interpret, and analyze digitized speech was difficult. However, the development of faster microprocessors, larger storage capacities, and better speech-recognition algorithms has made audio mining easier. Now, the technology is on the verge of becoming a powerful tool that could help many organizations. For example, companies could use audio mining to analyze customer-service and helpdesk conversations or even voice mail. Law enforcement and intelligence organizations could use the technology to analyze intercepted phone conversations. Public relations firms could use it to analyze news broadcasts to find coverage of clients.