Enrich Your Media Metadata with Speech Recognition Technology
The thing about time-based media is that it consumes a lot of time. Reviewing, organizing, and marketing video and audio content requires scrubbing back and forth. To find the clip you need, you must first burrow into your hard drive. Once you uncover the relevant file, you spend time fast-forwarding, rewinding, and watching in real-time to hear the words.
In fact, a study from GISTICS revealed that media creatives spend around 10% of their work time searching for and organizing files. And more than one-third of that time is wasted on files you never manage to locate.
Meanwhile, your media assets are growing at unprecedented speed. Seventy-one percent of marketing professionals say they need to create ten times as many assets as they did in the past to make an impact across the myriad of platforms.
This swelling archive holds great value. To maximize its potential means returning to it again and again to re-use the best moments. But efficient navigation of this archive requires first-rate media asset management.
A subset of digital asset management, media asset management is how you store, organize, and locate audio and video files. Your best weapon in this eternal battle is metadata. And if your media assets contain the spoken word, your secret weapon is the use of speech recognition technology to enhance and enrich your media metadata.
What is Metadata?
‘Meta’ is getting around these days, what with the impending metaverse and Facebook’s rebrand. So, it’s worth returning to the prefix’s original meaning and most common use in the digital realm.
In its Greek root, meta means ‘with,’ ‘after,’ or ‘beyond.’ For example, the word ‘metaphor’ comes from the Greek meaning ‘carry beyond.’ So, a metaphor is a verbal image that carries the meaning of what it represents beyond its literal representation.
More simply, in the case of metadata, we think of it as ‘data about data’ or ‘data about a file.’ Just as a metaphor exists one level beyond what it describes, metadata exists one concept beyond the data that your media asset holds. If you click ‘Get Info’ on a file on your desktop, you’ll see some good examples of metadata: the creation date, file type, and file size, and more.
Metadata is embedded in each file. Although mostly unseen, metadata acts as a searchable index to your hard drive or cloud-based storage.
Your software creates and embeds some basic metadata itself. But you enrich your metadata to be more helpful. This has long been a time-consuming process, especially if you work with lots of material. Today, media asset management tools take care of some of that burden. Integrate this tool with others, such as an asynchronous speech-to-text API, and it becomes fast and simple to convert the content of your video and audio into indexable metadata.
What Can Metadata Do for Your Business?
It is hard to overestimate the value of metadata for a business. Particularly a company involved in audio or video production. Metadata tags empower you to organize, classify, and track your files. They make it simple to locate or audit all files that share a particular characteristic range of values.
Metadata also has security benefits. Software generates some metadata when you create a file. Other metadata appears or updates during the file’s use-life. This makes it easier to track a file’s history and regulate user access/edit rights.
And, of course, metadata takes your search game to a whole new level. The more descriptive your metadata is of a file’s content, the more likely you will find it when you want it.
For spoken word content, little improves a file’s searchability like including a transcript with its metadata.
How to Enrich Your Metadata with Speech Recognition and ASR
Including a transcript in your metadata makes your video asset searchable by any word spoken within it. If the transcript includes a timecode, you can zero in on the moment you need among dozens of hours and hundreds of files. Unifying your content in a centralized, cloud-based repository of your raw material and finished masters is efficient and makes your assets less likely to disappear.
So, a transcript is a great idea. But isn’t manual transcription labor-intensive and time-consuming?
Yes – if you do it yourself. But this is no longer your only option. Due to advances in machine learning and artificial intelligence, automatic speech recognition (ASR) is approaching near-human levels of accuracy. For example, Rev AI has the world’s most accurate speech recognition engine. Developers train the engine on vast amounts of data generated by Rev’s team of 60,000+ human transcribers. It achieves greater accuracy than Google, Amazon, Microsoft, and others.
Content producers and businesses can integrate ASR with their media asset management tools to produce and process this metadata automatically using the Rev AI asynchronous API. Other producers prefer to order individual ASR transcripts for new projects as they complete them. You can do this in a few clicks at little expense.
Let the Robots Do the Work
A digital workflow is supposed to make file management more efficient. But often, this means businesses produce more files, and the net result is an unwieldy file system. To get back on top of your media asset management and save time for creative endeavors, harness the power of AI and speech recognition technology to enrich your metadata.