Vizrt, Nexidia combine dialogue search with MAM system

Vizrt announced greater integration of Nexidia’s patented Dialogue Search application into the latest version of Vizrt’s Viz One media asset management (MAM) system. Vizrt will demonstrate the integration at IBC 2014 in Amsterdam, stand 7.A10.

The new integration expands on the extensive search functionality in Viz One to now include finding assets or clips based on the actual words and phrases, quickly and accurately. The integration with Nexidia allows Viz One users to preview matching clips or assets based on search results and permanently save them within Viz One. Markers can be used as a base for immediate roughcut using Viz One’s browser-based player, or exported to an edit workstation.

“Search is key to the user experience. When building the Nexidia integration, we focused on ensuring that the entire dialogue search and roughcut process was seamless,” said Petter Ole Jakobsen, CTO, Vizrt. “This meant making sure all operations could be performed within our native web-based HTML5 interface. Thanks to the open architectures of both Nexidia and Viz One, and the very strong engineering teams on both sides, we were able to meet that goal.”

“A MAM is only as powerful as its ability to provide you with the right content,” continued Jakobsen. “If you can’t find the material you need – then the MAM serves little purpose. With Viz One – our open metadata forms, brand new logging tool, and best-of-breed search engine and interface all play their part in making sure users find content quickly. Nexidia dialogue search is a natural integration to further that goal. Ultimately that goal saves our customers money and ensures that they can air the best content first.”

”The Dialogue Search API provides Viz One users with a fully integrated search experience,” said Drew Lanham, senior vice president and general manager of Nexidia’s Media and Entertainment division. ”Customers will realize significant reductions in the costs associated with finding media since searches will no longer be dependent upon logged metadata or transcriptions.