Autonomy acquires Virage

Autonomy, a provider of infrastructure software, has completed its acquisition of Virage, a provider of asset management and rich media communication software. Now a division of Autonomy, Virage has embedded Autonomy’s Dremedia and Intelligent Data Operating Layer (IDOL) technologies within its asset management and business software for corporations, government agencies, universities, media and entertainment companies.

The technologies are integrated into the Virage SmartEncode and Virage Solution Server products for video production, archiving, Webcasting, publishing and news monitoring. SmartEncode software is used for automated capture, encoding and indexing of video. Solution Server provides a range of content management functions for enterprise-scale rich media applications, including data storage, full text search, content editing, and access control.

Dremedia’s technology is built upon IDOL, which automatically integrates unstructured, semi-structured and structured information from multiple repositories through an understanding of their content. At the heart of the software is its ability to process text, voice and video and identify and rank the main concepts within them. It then automatically categorizes, links, summarizes, personalizes and delivers that information.

Dremedia can take any broadcast stream in real-time, analyze all aspects of the content and dynamically create an XML index consisting of millisecond-accurate time codes describing attributes of the content (such as key frames, speaker IDs, an automatically-generated transcript, etc.). This can then be used to enable applications in speech and audio processing such as speech, speaker and language recognition and speech enhancement.

Because of the accuracy and utility of the speech recognition, Dremedia’s products enable the frame-accurate selection of video via an interface onto an automatically generated transcript. In addition, Dremedia’s proprietary technology—using advanced signal processing techniques—enables an image to be segmented into its component parts, such that they may be identified, understood, labeled and indexed.

For more information, visit www.autonomy.com.

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