Media and broadcast companies are using speech-to-text technology to improve their digital and media asset management.
Media asset management (MAM) is the storage and management of video and multimedia files. The exponential rise of digital data means organizations are having to seek out new tools and solutions to manage both existing media assets and the new ones being created every day.
According to a 2019 Cisco report, video content now accounts for four-fifths of global internet traffic – with the increase in video adoption driven by the growing number of people connected to the internet, as well as the increased popularity of over-the-top (OTT) video streaming services. More than half the global population – almost 4.57 billion people – now has access to the internet. And the number of devices able to access the web is up to three times as high as the global population.
These statistics of growing video adoption highlight the need for advanced solutions for broadcasters and media facilities to improve operational efficiency by streamlining their digital asset management workflows.
Traditional media and digital asset management tools are designed to deal with static files such as images. They have limited ability to handle large media assets like audio and video files and they struggle to deal with the ever-increasing volume that needs to be handled daily.
Today, a new breed of tools is available with advanced features suited to multimedia use cases – artificial intelligence, machine learning and speech recognition technology can be used to extract advanced metadata information. This metadata is integral to getting the most out of modern video and audio assets.
To cope with the increasing volume of assets, organizations need more information to identify what makes each asset different – for example, what they contain, keywords, themes, content or contributors. It’s this information that makes assets easier to locate and enables companies to quickly find out what is contained within an asset.
Giving asset managers and producers access to the right automated technologies lets them focus on curating the best content in the least amount of time, rather than spending hours searching for what they need.
Voice technology enables organizations to take any media content – whether audio or video – and convert it into text. Converting voice within media content into a written format enables businesses to use raw material to create metadata tags, curate social media content, add captions, search for keywords within an asset and so on. This can be achieved consistently and at scale.
Traditional tools enable users to extract information such as the time a file was created, who created it, what software was used, and the format, duration and file type. But this doesn’t tell you anything about the actual contents of the file. Voice technology reveals a deeper context around the content of the file – it makes all the voice data within an audio or video file visible to help content producers, editors and other video professionals find the elements they need in a simple search.
To deliver value and revenue from media assets, organizations need to be able to quickly and easily locate assets. Automatically transcribing audio and video files using voice technology means all assets are accessible via text-based search. The use of voice technology for the automatic transcription of media assets means large volumes of assets can be better understood and indexed – making them easier to discover, edit and share on digital channels.
Voice technology provides significant efficiencies in the production workflow for digital and media asset management in organizations. As shown in the graphic above, the benefits include:
Download our Smart Guide to find out more about these benefits of using voice technology to improve media asset management.
Alex Fleming, Speechmatics