Large broadcast news operations ingest huge volumes of content every day, all of which must be logged and reviewed to determine which assets, illustrated by which video clips, will be presented to viewers. It’s a tedious and time-consuming task, performed by dedicated teams who manually review incoming content and then describe or notate that content, which producers later access to produce finished news segments.

This process is compounded by the wide variety of delivery platforms – linear broadcast, OTT, various Multichannel Video Programming Distributor (MVPD) services, social media platforms and others – and each with its own formatting rules and other requirements. And of course, with news, time is in short supply and every second counts when turning around content and getting news to air. 

Applying AI and ML technologies to news workflows can auto-generate highly accurate metadata of video content more quickly and less expensively than traditional methods, which yield big cost and time benefits for fast-paced news operations.

The key to delivering these benefits is in the ability to harness the power of these next-generation technologies. By leveraging high-performance AI capabilities in the cloud (speech-to-text, facial recognition, object identification, content classification, etc.), combined with powerful knowledge management orchestration tools, these metadata solutions deliver actionable intelligence for media operators and accelerate the search, retrieval, production and delivery of news content.

The solution described above is what one major broadcaster is using to enhance its existing news production workflow and incorporates several AI engines and three specific toolsets as follows.

AI engines include:

• Automatic speech recognition (ASR)
• Natural Language Processing (NLP)
• Text Translation
• Facial recognition
• Emotion recognition
• Logo detection
• Object identification
• Optical character recognition (OCR)

Toolsets include:

• Automated metadata creation for raw feeds and post-production content residing in PAM/MAM that applies advanced AI- and ML-based content analysis for automatic generation of better-structured, more detailed, and more accurate metadata. Media operations benefit in two key ways — first, with tremendous time savings in up-front metadata generation, and then by giving producers the ability to zero in on the assets they need right away.
• Closed caption/subtitle generation platform, which unites cutting-edge STT technology and other AI-driven processes with cloud-based architecture. This toolset radically reduces the time and cost of delivering accurate, compliant captions for publishing worldwide.
• Broadcast monitoring and compliance logging that allows operators to record, store, monitor, analyze, and repurpose content quickly and efficiently with a minimum of clicks. Integration with AI microservices enables powerful insights and video intelligence applications, including:

○           The ability to record, store, and retrieve content for compliance, quality of service, and insights into broadcast content.

○           Automatic transcription of content from live broadcasts and commercials.    

○           Automated detection of logos, objects, faces, and shots.

○           Automatic extraction of on-screen text.

○           The ability to identify ad breaks in logged content.

○           The ability to identify restricted words or topics in recorded/logged content, as well as the classification of incoming ad material for restricted content. 

○           Generation of automated reports for loudness compliance, QoE, SCTE inserts, and ad detection and identification.

○           Automatic content classification.

○           The ability to assess the quality and conformance of captions.

The solution uses a variety of AI and ML technologies to process numerous, 24x7 live news feeds simultaneously from a wide array of sources.  Concurrent, real-time processing of this quantity of content, is something no amount of personnel could ever hope to accomplish.

As feeds are received and ingested, they pass through APIs to all the applicable AI engines and on to an orchestration layer, where the solution automatically harmonizes and synthesizes the metadata and doles it out to the software tools mentioned above. Those high-value applications — the transcription, video metadata generation, and monitoring tools — take over, working in unison or individually as directed by the operator to provide intelligence and actionable insights that make the metadata usable. These capabilities enable intelligent and immediate logging and feedback of content quality and compliance, better positioning broadcasters to meet regulatory, compliance, and licensing requirements for closed captioning, decency, and advertising monitoring.

Importantly for news producers, the solution generates text in the form of transcripts of the spoken word.  Transcript metadata essentially becomes a script of the content, which is time indexed back to the media within the edit and production environment.

In this enhanced state, producers and editors can quickly search for and retrieve relevant media assets needed to create their news stories, thereby accelerating the entire production process.  This all happens automatically in real-time, with results being transferred back into the editing environment. Everyone within the editing ecosystem can get their work done faster, easier, and more effectively than with using traditional methods. Editors and content producers are now only limited by how fast they can make decisions.

While this solution is deployed for an ever-growing feed of live content, all of these capabilities could just as easily be applied to existing recorded content.

Using powerful AI capabilities available through an intuitive and functional software layer, easily accessible across the media enterprise, media professionals can expedite critical processes, reduce mundane tasks and accelerate the creative process – all while saving critical time and expense.