Automated Generation of Videos from News Stories
Abstract
Recent advancements in internet, media capturing, and mobile technologies have let fast growing News industries to produce and publish News stories rapidly. In recent days News industry is trying lot to make their news stories attractive and more engaging to their readers. Youngsters these days often do not have much time to go through an entire news article to understand the content, yet they want to know all the important elements the article.
Recent surveys suggest that Millennials and other similar age group of people prefer news stories as videos over news as text. However manual generation of videos for each news article is considered costly and laborious. Hence there is a requirement for news video generation system that can create interesting, engaging, concise and high- quality news videos from text news stories with little or no human intervention.
Recent startup Wibbitz assists publishers in converting news stories into videos with the help of semi-automated content analysis and manual editing with minimal production time. This project is developing an end-to- end automated solution for generating videos from news articles. The system has different NLP based components for automated news content analysis. Detection of key phrases from the news article are done using NLP based or Deep learning solutions. Named entities in a news story such as person, time, place, brand etc. can be automatically detected using NER for highlighting them in videos.