BBC News Labs started a stream of Language Technology projects in 2014, in order to scale our storytelling globally
Transcriptor takes news audio content, transcribes it, then provides a means to view and edit the transcript alongside the original content.
ALTO is a virtual voice-over tool for reversioning video content into multiple languages using text-to-speech voice synthesis
SCRIPT is a 3-year research and innovation project looking to develop synthetic voices for low-resourced languages.
A programme of international innovation activities, aimed at harnessing localised industry talent to explore new opportunites.
Window on the Newsroom is a prototype discovery interface to help Journalists find content quickly across the whole Newsroom system by story or metadata properties
The Juicer takes news content, automatically tags it, then provides a fully featured API to access this content and data.
This Big Data project will leverage machines to do the heavy lifting in multilingual media monitoring.
Stitch is a tool that allows journalists to create rich graphics video templates directly from their web browser.
The News Slicer takes MOS running orders and transcripts from BBC TV Broadcast Playout, then auto tags and auto segments the stories.
JUN 05 2017
BBC News Labs has six open positions for flexible and imaginative developers with an enthusiasm for media.
JAN 16 2017
A roundup of our projects and experiments in 2016.
JAN 13 2016
How can News Labs use its achievements in 2015 to set its priorities for 2016?
SEP 17 2015
BBC News Labs at the Data Science for Media Summit
SEP 07 2015
BBC News Labs looks at how our experiments and projects fit into Tony Hall's Charter proposals for the future of the BBC
JAN 13 2015
NOV 18 2014
A prototype workflow for reversioning content into multiple languages, and controlling an "on demand" multilingual news service.
Create spoken content anywhere, at any time, without access to specialist facilities such as TV and Radio studios or even microphones
The BBC has AN ENORMOUS amount of amazing content that can explain and contextualise the News. How do we connect and harness this?