NEVADA CITY, Calif.—Telestream has announced Stanza, a captioning and subtitling software product that is designed to lower barriers to entry with a subscription-based OPEX business model.
The product is also designed to address the challenges of remote working. Stanza’s client-server deployment model allows captioning editors to work from any location from a simple browser-based editing console, regardless of where media files are stored. Stanza uses the powerful Telestream GLIM engine to play back original high-res files instantly without any need to create and transfer proxy images, the company said.
“With Stanza, large media files do not need to be downloaded or moved across a local area network, nor do proxies need to be created to work on captioning projects,” says Scott Matics, senior director of product management at Telestream. “And with its built-in access to Timed Text Speech auto-transcription and integration with Vantage and Timed Text Flip transcoding and processing, Stanza represents a powerful new way to automate more of the caption creation process.”
With the ability to run on Windows, MacOS and Linux, Stanza provides greater flexibility by being platform agnostic and it includes optional access to the AI powered Timed Text Speech auto-transcription service which supports over 100 languages.
In addition Stanza integrates with the Vantage Timed Text Flip text transcoder and processor to provide automation for captioning workflows.
“With Stanza, companies of all sizes, as well as independent transcriptionists, can now create and edit broadcast-grade, high-quality captions and subtitles more efficiently and more cost-effectively than ever before,” added Matics. “This represents the future of closed captioning and subtitling workflows.”
Stanza is built upon the Telestream Media Framework, the same technology that underpins several Telestream products and services such as the Vantage Media Processing Platform and Telestream Cloud Transform. The Media Framework includes format and container support that has been tested in some of the most challenging broadcast use cases around the world.
More information is available here.
