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Interra Systems presents cutting-edge Media QC, monitoring, and analysis solutions at IBC2024

Interra Systems, the leading provider of end-to-end quality assurance solutions to the digital media industry, will showcase its latest innovations in content-aware QC, monitoring, captioning, and analysis at IBC2024. Attendees can visit Interra Systems to explore the newest features of the company’s BATON and BATON Captions solutions, alongside its award-winning ORION content monitoring solution, designed for comprehensive monitoring of linear/IP and live/VOD streaming content. The company’s VEGA media analyzer, offering detailed analysis and compliance validation of compressed video, and the company’s new Relay Workflow management tool will also be on display.

“At IBC this year, we are excited to showcase our BATON Captions solution, which harnesses the power of machine learning, automatic speech recognition, and NLP to significantly reduce the need for human intervention while providing accurate captioning enhanced with QC checks. Multi-language support is critical for broadcasters and service providers, especially in Europe, so we’ve improved our captioning product further to support a range of languages, including Spanish, French, Finnish, Polish, Portuguese, and many others,” said Penny Westlake, senior director of Europe at Interra Systems. “We will also demonstrate how our solutions are consistently being developed in response to key trends in the evolving media and entertainment environment. For example, our ORION suite of solutions addresses the monitoring needs of next-gen media workflows, driven by cloud infrastructure, automated error handling, ad-insertion checks, root cause analysis, and high-quality video output, and designed for compatibility with CMAF, SRT, and SMPTE’s ST 2110 standard.”

Streamlining QC Workflows With BATON
At IBC2024, attendees will get to experience the latest version of Interra Systems’ BATON solution in action. Featuring advanced AI and machine learning capabilities, this updated version continues to lead the industry in automated QC platforms, meeting the highest standards for quality and compliance.

The solution includes several new enhancements, such as the new BATON 9 series, which offers significant framework updates, enhancements in performance of video quality checks for 4K files, support for RDD59 specifications, and direct analysis of image sequence formats, apart from optimized MXF file verification, advanced diagnostic tools for system health monitoring, and API improvements.

Interra Systems will also reveal new features added to its BATON Captions. Leveraging cutting-edge ML and automatic speech recognition technology, new features of BATON Captions include web-based player enhancements and new correction options, including segmentation and shot boundary correction.

In addition, BATON Media Player will be on display, which simplifies how media professionals can play, inspect, and verify audio and video content.

Improving QoS and QoE With ORION Content Monitoring
Today, media companies handle a significant volume of complex content. Programs may undergo re-encoding, transcoding, and multiplexing, which can negatively impact content integrity and user experience. At IBC2024, Interra Systems will showcase new capabilities featured in the company’s ORION suite of solutions, which support a wide range of deployment scenarios in hybrid and cloud environments. These enhancements cater to linear broadcast, IP-based delivery, and live/VOD OTT content.

ORION-OTT — Interra Systems’ software-based OTT monitoring solution for checking content integrity and related network performance of ABR content for multiscreen service delivery — now includes localization support, certification for the latest OS releases, and Dolby Atmos integration. Significant updates improve dynamic ad insertion (DAI) and server-side ad monitoring, low-latency stream monitoring, and provide support for the latest DRM solutions, solidifying ORION as a comprehensive content delivery and management solution.

Stand 7.C11