Generation of videos from news stories - winter internship at Bennett university

Описание: 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.
This research will develop an end-to-end automated solution for generating
videos from news articles. The system will have different NLP based
components for automated news content analysis. Detection of key phrases
from the news article will be 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. Detection of
emotions in news text or phrases for automated suggestion of background music
or emojis for video production. In addition, famous tweets related to the news
covered by the article can be detected and included in the final video. Also
images and videos related to news content should be automatically discovered
by crawling from internet and can be instantly used as background scenery in
the video. This effort will also consider the analysis of the aforementioned steps
in a faster manner for real-time video production.