Imagine that you work for a sports media company and your next project is to create a montage of the US women’s soccer team over the past 20 years. To do this, you must scour through thousands of stats and hours of footage, and hundreds of articles and photographs. If your company had invested in AI auto-tagging, you would be able to sift through extensive media archives with ease.
According to Veritone, “AI auto-tagging is the process in which artificial intelligence is used to tag media files with metadata. This is a modern approach to metadata tagging, which creates a term that describes a keyword or phrase and assigns these metadata tags to a media asset.” AI auto-tagging sets up media files to be easier to find by either a project manager with private access or by an external user.
Auto-tagging uses common AI identification engines like audio fingerprinting, facial recognition, speaker recognition, logo detection, and object detection to provide information about the file’s contents. While AI may still not be 100% accurate, auto-tagging provides a speedy, high-volume alternative to manual tagging processes. Not only can you search through tagged files more efficiently, the process of meta-tagging content is much more streamlined. AI auto-tagging is a valuable option for companies with more data than they can manually handle.
One Response
It sounds like this advancement is a positive one for those who are doing research. This new AI will make searching much faster and easier especially with doing the kind of research that you described.