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Tedial Press
Tedial is a leading provider of MAM solutions (Media and Content Management) designed to maximize business efficiency and profitability.

Tedial Launches SMARTLIVE MULTI SPORT Configurations at IBC 2019

Tedial, a leading independent MAM technology solutions specialist, is launching SMARTLIVE MULTI SPORT configurations at IBC 2019. This sophisticated addition to Tedial’s cutting-edge, award-winning sports and live events solution allows users to generate automatic highlights or auto-clipping for ANY SPORT quickly and easily.

At IBC, visitors will see a dramatic increase in the number of highlights that can be produced in a multi-sports environment with SMARTLIVE.  This is a key addition to the list of the solution’s fast-growing capabilities. Totally agnostic to all data feeds, Tedial’s metadata engine makes it simple to add new SPORT configurations to the system as and when required.

In addition, SMARTLIVE and Tedial’s Evolution MAM now includes a new module that allows all types of content to be published to any social network in just one click. Enabled by the system’s capability to create social media campaigns directly inside the MAM, publishing to social platforms has become really easy, quick and efficient.  This will be demonstrated on the stand throughout the show.

Tedial will also demonstrate its technology partnership with Speechmatics. By integrating Speechmatics’ industry-leading Automated Speech Recognition (ASR) technology with SMARTLIVE, operators can seamlessly search for comments made by the commentators during a sporting match or live event. 

Providing operators with faster access to content, Tedial is showcasing its new SMARTLIVE bundled solution that can easily be deployed on top of the customer’s existing production environment. This is key as it provides sports broadcasters with a highly efficient solution that can be up and running very quickly. As well as these new features, Tedial will highlight the financial and operational benefits of operating SMARTLIVE both on premises and in the cloud.

Esther Mesas, CSO/CMO, Tedial says, “We are delighted to announce the new SMARTLIVE MULTI SPORT feature that will continue to assist media companies with further enhancing their story-telling capabilities. As sports rights become ever more expensive and fans expect more insight and more analysis, SMARTLIVE is the most comprehensive, most productive way to create additional content to satisfy consumers and increase revenue opportunities.”

Built on open standards, SMARTLIVE is agnostic to the equipment around it. It can be added to any production infrastructure. Its virtualised software architecture can be implemented on premises, in the cloud, or as a hybrid. As well as generating its own metadata it connects to existing archive asset management systems, using examples from the past as a way to illustrate today’s news.

Machine Learning or AI?


Written by Jerôme Wauthoz, VP Products, Tedial

The industry is buzzing with talk about, and deployments of, AI and machine learning technologies, which are making strides in production environments. But have you thought about the difference between the two?

In the parlance of computer science, machine learning uses statistical techniques to give computer systems the ability to progressively improve the performance of handling a specific task by collecting and analysing data, which always creates improvement without explicit programming. Machine learning is closely related to computational statistics: the basis of prediction through the use of computers. It is sometimes conflated with data mining, where systems are designed to focus on data analysis and is sometimes referred to as unsupervised learning.

Artificial Intelligence

On the other hand, artificial intelligence (AI) is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. AI research is the study of “intelligent agents” or any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term artificial intelligence is applied when a machine mimics cognitive functions that humans associate with other human minds, such as problem solving.

What can be considered AI is changing all the time: as computers become increasingly capable, tasks thought of as requiring intelligence are now often removed from the definition. For example, optical character recognition is today not considered artificial intelligence because it has become routine technology.

In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and better theoretical models. The techniques of AI have become an essential part of the technology industry, helping to solve many challenging problems in computer science, software engineering and operations research.

While we can consider AI to be a blanket term that encompasses many media applications, the reality of our industry is that most of these software applications are not currently truly intelligent and must be taught to carry out their particular function. In a real sense, we are applying machine learning tools to process or manage mundane, repetitive chores that have no intelligence other than the data we as trainers supply.

A clear example is often discussed in our industry: the review and metadata annotation of all the assets stored in a deep archive through years of programming. A software tool assigned this task must “learn” to identify the images, recognising the important from the inconsequential, and must have a clear set of objects to note. Cloud-sourced systems that leverage crowd input can be useful to our modern media applications, such as recognizing a location or a celebrity.

However, a unique library of historical media may have no external reference or crowd-sourced knowledge and therefore must be personally taught to recognise the criteria for evaluation and annotation before it can be a useful tool. As media executives and broadcasters, we must recognise that regardless of what we call this service, it is really machine learning we are implementing and there’s effort needed to train a computer to be a useful tool in our applications.

What’s happening now?

Although many companies are investigating applications and requesting proof of concept demonstrations, not many end users have taken the plunge into the deep waters of machine learning because the applications and return on investment are still unknown. What we are all looking for is the “killer app”; the clever application that increases efficiencies, reduces labour or creates new opportunities for monetising an existing library.

As AI systems evolve, more of these specific applications are becoming apparent, and at Tedial we like to think of them as “clever AI”.

Clever AI

Let’s take a look at some examples of clever AI. Software tools have been used for years to convert speech to text and systems have been applying this technology to annotate frame-accurate proxies with the text-for-media searches. A clever application is to enable the underlying data model to recognise and trigger automated orchestration workflows based on the occurrence of specific key words, typically a specific action in a sporting event, and automatically creates an edited clip of the action or automatically distributes the media to appropriate locations or downstream services.

Many cloud-sourced AI services can be leveraged in clever ways to augment or annotate video and audio, recognising celebrities, locations, music beds etc. These tools can make searches faster and more relevant and reduce risk by recognising and alerting management to license infringement problems and/or managing the details of image release documentation. But these applications don’t provide a clever AI result. The ability to evaluate media and judge its “sentiment” is currently an important machine learning exercise under investigation by many media outlet; the clever AI application is taking that recognised sentiment and using it to replace human-generated recognition and action steps. The clever AI application would be to train a system to recognise players, athletes or fans in the crowd to bring more editorial value to a feed. For example, in live sports, a system could be trained to recognise colourful pictures of fans cheering or an athlete celebrating and automatically add the scene into the event highlights at the right position.

At Tedial, as we build more functionality into our SMARTLIVE live sports event system, we are working to enhance our AI integrations to provide measurable clever AI.

Tedial brings broadcasters measurable financial advantages with AI-powered SMARTLIVE

Tedial, a leading independent MAM technology solutions specialist, is showing a line up at NAB that provides measurable financial advantages and operational efficiencies. The company is showcasing SMARTLIVE, its cutting edge AI powered automated live sports solution; HYPER IMF MAM, the world’s only certified end-to-end IMF workflow, with an enhanced feature-set; an upgraded version of its globally embraced Version Factory automated single workflow for multiple platform delivery; and upgrades to the Evolution aSTORM hybrid content management solution.

SMARTLIVE – AI powered automated live sports solution

Powered by AI, SMARTLIVE is the world’s most comprehensive  workflow solution tailored for sports and live events. The solution leverages its unique metadata engine to automate highlight creation and distribution – including tight integration with digital platforms and social media. SMARTLIVE is now shipping.

SMARTLIVE’s capabilities allow it to: automate the event metadata ingest process; automatically provision a production environment for the production team; manage multi-venue feeds; and automatically generate personalised content of one or multiple games, or even an entire season of highlights; and feed campaigns to social media platforms.

SMARTLIVE provides measurable financial advantages by enabling the same production team to create more content resulting in increased fan engagement and additional revenue. It also permits quicker access to content allowing a shift to more affordable digital models.

Tedial HYPER IMF MAM – New features guarantee operational efficiencies

Tedial’s HYPER IMF, the world’s only certified end-to-end IMF workflow, is at NAB with an enhanced feature- set that includes support for 2018 SMPTE IMF standards, including Apple ProRes wrapped in MXF. Business Cases that apply to IMF processes have been incorporated so content can be efficiently managed and MAM-workflow orchestrations can be easily supported, such as attaching late deliveries of forensic watermarked components to previously distributed media, detecting and managing duplicates, and waiting for master assets to arrive. Assembly of completely new IMF packages is accomplished using low-resolution proxies and a Web-based GUI. Powerful dashboards have been added for real-time monitoring of operations and system wide capacity monitoring. HYPER IMF has a proven agnostic infrastructure; it can be deployed on-premises, in the cloud, and in hybrid infrastructures.

Tedial Version Factory 2019

Tedial’s award-winning Version Factory, the world’s only single workflow that automates thousands of OTT and VOD versioning tasks, is back at NAB as Version Factory 2019. The new version features upgrades that include: managing ‘on-the-fly’ assembly of unique versions, including pre, post and mid-roll insertions; matching contractual distribution requirements for timely deliveries; enabling IMF-compliant low-resolution proxy edits on media and templates so seasons of episodes can be managed with a single configuration.

Users that deploy the Version Factory and HYPER IMF will benefit from support for existing and new platforms, delivery of content in the correct format with audio tracks and subtitles in the correct language, as well as any additional components required (artwork/trailers etc.).

Evolution aSTORM conquers hybrid content management

Evolution aSTORM, Tedial’s scalable, reliable, future-proof and cost-effective content management solution has been upgraded with numerous cost-saving features. aSTORM changes the storage paradigm from the traditional HSM approach to a true multi-tier, multi-site object-based storage environment. It transparently manages various storage tiers across departments and continents! New features at NAB, include: Optimising transfers between sites for reduced transfer costs; and improved tape migration workflows between technologies for increased resource efficiency resulting in lower migration costs. aSTORM also now supports Oracle cloud storage.

How do AI and MAM provide improved live sports production?

SCREEN AFRICA EXCLUSIVE: Everyone is talking about Artificial Intelligence (AI). This disruptive technology has entered an unprecedented stage of development and is imposing itself in our daily lives at a pace that surprises, fascinates and sometimes frightens. AI is a hot topic with inspiring and practical use cases emerging every day.

According to recently published IABM data, AI adoption in broadcast and media is still at an early stage. Only 8 per cent of media technology buyers said they had adopted AI before last year’s IBC; 36 per cent said they were unlikely to adopt it in the next two to three years; and 56 per cent said they were likely to adopt it in the next two to three years.

As we can see the broadcast and media industry is on an adoption curve. However, there is no doubt that AI will change the media landscape while providing enhanced viewing and increased opportunities for monetisation. Vendors need to consider how they add value for their customers and ensure that AI’s not just another similar solution.

With all this AI news swirling around it’s no surprise that this year, the industry buzzword will continue to be “AI.” For media asset management providers AI could be a game changer, in a recent IABM report, MAM was specified as the fourth most important priority for buyers.

The attractiveness of AI for broadcasters is the efficiency of using computers to understand audience demands, the management of data and filtering of content for specific themes, as well as creating more, original and personalised content for increased viewer and fan engagement to reduce production costs and increase monetisation.

AI and machine learning will be leveraged by industry leaders to extend their products. Recent industry news coverage has shown that a series of different applications are on track to be introduced. Many of these will focus on specific applications but most will fall into the categories of increased metadata generation and application, media augmentation and annotation, or machine learning applied to workflow operations to further automation.

The increase of sports rights due to the arrival of new comers to the digital economy such as Amazon, Facebook and Twitter are a new challenge for broadcasters who need to reduce their production costs to maintain their profitability.

So how do media companies add value for their customers and ensure that AI’s not a “me too” solution? The answer is technology investment that efficiently automates common, repetitive tasks. Automation tools with AI will help production teams to produce more content and personalised content that allows media companies to gain more fans, viewer engagement and increased revenues.

Sports production is demanding, it’s about live content and speed.  This is a good example of where AI combined with MAM can help media companies to face today’s challenges.

Assembling sports highlights is a prime example, broadcasters can automatically pre-configure events in the MAM to drastically reduce preparation time and avoid human errors. The question is, how do MAM providers create sophisticated AI options for broadcasters and media companies that enable these efficiencies? An AI powered metadata engine to fully automate in-game production is key.

During the live game, the programme feed is passed through a computer vision AI engine and a speech-to-text AI engine, which provide additional metadata and contextual information about the game to augment media logs.

Combined, these different technologies enable automatic logging of a live event and generation of event logs during the game. This supports Tier2 federations or smaller broadcasters and clubs who do not have funds to buy the service of an external data provider. It also allows companies still manually logging the game to optimise their resources.

AI will also assist in automatic content tagging, which is traditionally a labour heavy and expensive process.  Enhanced MAM Search capability opens the door to more content creation, thereby increasing monetisation opportunities.

Together, these technologies enable automatic highlights creation with the best IN and OUT point calculated by the AI engines. Clips and EDLs are automatically created and automatically published to social networks, efficiently increasing the amount of content created with the same staff.  Tightly integrated with AI tools, an advanced MAM can automatically generate an increased number of highlight clips during or after an event and deliver this advanced storytelling to a very targeted audience increasing the potential for significant growth in fan engagement while reducing production costs.

Fans are requesting more and more personalised content to be consumed anywhere, anytime on any device. Using AI to analyse hit rates on social networks and make suggestions for search engines to provide better results to producers will allow them to create tailored content.  This means more opportunities for fans accessing enriched content on their preferred social platform, increasing engagement and driving more revenues from ads or sponsors.

As sports moves towards increased data in every aspect of the game (players, tracking, game data), AI will enable content to be captured and analysed and will allow enriched data to be automatically added thanks to a powerful data analytics engine.

Finally, AI can be used to increase workflow efficiency by analysing processes and predicting failures within a process. Connected to a Business Process Manager, AI can learn from errors in workflows and improve processes, minimising errors in the future and increasing efficiency.

Properly focused and applied AI helps modern broadcasters effectively reduce production costs while increasing revenue, enabling them to cope with the never-ending increase in sports rights costs and demanding user experience.

AI will also help to improve media workflows and streamline the user experience to offer augmented solutions and greater creative opportunities for viewers who are constantly looking for a richer and immediate experience.

As a leading provider of media and content management solutions built on its multi-award-winning Media IT platform, Tedial is uniquely positioned to answer the needs for smart live production solutions of global media companies and broadcasters.

Written by Jerome Wauthoz,VP products, Tedial

Tedial’s new SMARTLIVE marries AI to MAMs

Tedial, a leading independent MAM technology solutions specialist, is launching SMARTLIVE, a cutting-edge live sport solution and major revolution in sports production at NAB 2018. The unique development marries Artificial Intelligence (AI) to an innovative metadata engine to bring the back office and archives closer to live than ever before. This tight integration supports an increased number of highlights, during or after an event, and allows a specific story to be delivered to a targeted audience via multiple platforms including Social Media, increasing the potential for significant growth in fan engagement. SMARTLIVE is being demonstrated in Booth N 1420.

An Entire Season – Prepared in Advance!

SMARTLIVE simplifies event preparation by capturing team, event and statistical data and automatically building an event inside its metadata engine.  Simultaneously, SMARTLIVE automatically creates the corresponding log sheets, player grids and the video feed capture schedule for the event.  All these preparations are linked and organised in collections, so an entire season of sports events can be prepared automatically in advance. Agnostic to any sports and to any data providers, SMARTLIVE’s powerful metadata engine can be easily configured to create an automatic metadata ingest process and address demanding and complex sport workflows.

SMARTLIVE directly connects content to Artificial Intelligence engines: video and audio recognition can be leveraged to generate locator data and annotate live media proxies across multiple camera or venue inputs. During events, all event data from the PAM is ingested in its native format, automatically augmenting the proxy logs, and the system can be configured to automatically create clips based on actions, keywords or logged occurrences. Once created, these highlights can be automatically published to social media, or passed to workflows that enhance the director’s programme and the broadcast. Automatic highlights can be of a single event, a particular star player, or an entire season!

SMARTLIVE dramatically increases the utility of the MAM GUI interface, bringing the MAM much closer to LIVE production than ever before. It is 100 per cent compatible with PAM providers such as SAM or EVS which makes it the perfect tool to orchestrate all business processes on top of an existing PAM, including the use of historical archives in live production. It can then manage the media life-cycle or media movements between different sites.

Not only does SMARTLIVE bring historical archives into PAM logs live in the format the PAM can immediately use, it also fundamentally reduces production preparation time, and allows Broadcasters, Rights holders, Clubs and Federations to significantly increase the number of highlights created during or after a sport event with less staff thanks to its automatic highlight engine and AI integration. More content published means more revenues.

At NAB, Tedial is showing SMARTLIVE automatic highlight creation, integrations with AI engines, the speech to text integration annotating the incoming live media with technology partner Speechmatics, and the automated publish feature with technology partner TELLYO.

Jerome Wauthoz joins Tedial as vice president, Products

Tedial, a leading independent MAM technology solutions specialist, has named Jerome
Wauthoz vice president, Products, effective immediately. Esther Mesas, CMO/CSO,
made the announcement from headquarters in Malaga, Spain.

As vice president, products, Wauthoz will focus the innovative Tedial development
team on new products and services for the media and entertainment industry, as well
as bring executive level strategic marketing to the organisation.

Wauthoz joins Tedial following more than 22 years at EVS Broadcast Equipment. An
experienced team leader and product manager, he brings with him a deep
understanding of live production workflows and extensive experience analysing
customer needs across global markets. He launched his career at EVS as a software
engineer and subsequently held management-level positions, including R&D manager;
product manager and market solutions manager. He most recently served as vice
president of products, responsible for overseeing the team tasked with developing the
Company’s next solutions.

“Jerome’s background makes him uniquely qualified to assess customer needs in a
live production environment and develop solutions that elevate production values and
provide considerable cost savings,’ said Esther Mesas, Tedial CMO/CSO. “We can’t
think of a more perfect candidate to drive our expanding portfolio that includes the
new Tedial Evolution Live Event Archive solution, a tight integration between the PAM
live production workflows and our MAM system.’

Wauthoz holds a Masters in Engineering degree in Electro-Mechanics from Liege
University, Belgium where he also served as an assistant teacher.

Tedial Version Factory named IABM Game Changer Winner 2016

IABM announced winners of its Game Changer Awards at its annual awards ceremony on 19 April 2016 at the Las Vegas Convention Center. Tedial, independent MAM solutions specialist, announced that its Version Factory won the IABM Game Changer Awards 2016 in the System Automation and Control category. This is the second year running that Tedial has won the Game Changer award picking up the prize in 2015 for its Tedial Evolution™ platform. Version Factory was identified by the initial judging panel as one of the leading products or services to be exhibited at NAB Show 2016, one of three entries to be shortlisted in its category.

Tedial Version Factory was officially launched at NAB 2016, and is the culmination of 15 years of innovations and creative application of industry standards. Version Factory is a single efficient and cost effective workflow that supports millions of file input to output configurations and can be managed from a single operator screen. Designed to interface to content management/rights management/traffic/work order systems for automated operations, the Version Factory stacks chosen media engines (transcoders, quality control, DRM, CDN, etc.), employs SMPTE standardised designs for future proof “N-input to N-output’ operations and provides the maximum flexibility and scalability for OTT/VOD Platforms, Network Operations and media companies focused on managing their Brand across all distribution formats.

The nine category winners including Tedial will be automatically submitted as candidates for IABM’s prestigious Peter Wayne Award, with the winner announced at the IABM Annual International Business Conference and Awards in December 2016.

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