Swedish startup Newstag uses artificial intelligence (AI) to allow customers to create personalized video news channels from major global news providers. Their mission is to continuously empower people and organizations with the latest, diverse information. To increase discoverability of video news from all around the world for their customers, Newstag creates rich metadata for each video. Newstag was able to automate this manually intensive process of extracting and creating metadata from videos by using Amazon Transcribe, Amazon Translate, and Amazon Comprehend. Using a combination of AWS services, Newstag can create rich metadata for ten times more videos than was previously possible.

“We believe people want to choose what news they want to see. Enabling customers to curate relevant stories is pivotal for us to carry out our company mission,” says Mats Ekholm, Chief Technology Officer of Newstag. To accomplish this, Newstag has developed tags that customers can select to create a personalized video news channel. The following screenshot illustrates how customers can select these tags in Newstag.

To curate over 1,000 videos a day, Newstag’s editorial staff had spent a lot of time manually tagging content in various languages. Tags mostly consisted of titles, brief descriptions, and limited metadata. Struggling to keep up with demand, the startup looked for a simple, cost-efficient, and easy-to-deploy solution. By using pre-trained machine learning (ML) services on AWS, Newstag was able to use AI to solve the problem even though they had no previous experience with the technology.

First, Newstag uses Amazon Transcribe to create transcripts of speech in supported languages from the videos stored using Amazon Simple Storage Service (S3). Then Amazon Translate is applied to non-English transcripts as well as other titles, descriptions, or keywords originally provided with the video for accurate translation into English. Finally, Amazon Comprehend, a machine learning service that provides insights from analyzing textual content, is used to extract entities from all texts available in English. These named entities, such as organizations, people, places, and locations, are used to create accurate tags to help customers find targeted content.

“We used to manually create tags for about three to four videos per hour,” explains Ekholm. “With AI language services offered by AWS, we can now create tags for about 30 to 40 videos per hour. It means a 10-times increase in the number of news stories that our customers can see on Newstag.”

Ekholm automated a majority of the tagging process for video news in different languages within five hours at low cost. “I was impressed by how easy it was to deploy Transcribe, Translate, and Comprehend. I was also very pleased with their low costs. As a start-up, we have to be smart about operating costs,” says Ekholm.

Learn more

See the AWS website to learn more about language services for AI. Here are some useful blog posts from AWS to get you started:

• Build text analytics solutions with Amazon Comprehend and Amazon Relational Database Service
• VidMob combines computer vision and language AI services for data-driven creative asset production
• Build a social media dashboard using machine learning and BI services

About the Author

Woo Kim is a Product Marketing Manager for AWS machine learning services. He spent his childhood in South Korea and now lives in Seattle, WA. In his spare time, he enjoys playing volleyball and tennis.