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Adaptive Podcasting: the Future of Personalised Podcast Experiences

ADAPTIVE PODCASTING IS AN EMERGING PODCAST FORMAT THAT ENABLES PRODUCERS TO MAKE PARTS OF THEIR AUDIO PERSONALISED TO EACH LISTENER. THE FIRST TOOLS DEVELOPED BY BBC RESEARCH & DEVELOPMENT (R&D) ARE AVAILABLE NOW AND OPEN-SOURCED FOR ANYONE TO USE, EXPLAINS REBECCA STAGG.

Wmagine if the stories you listen to could adapt to your surroundings. To the time of day you’re listening to them, whether it’s light or dark outside; or if they could stretch or contract in length to fit with how long you’ve got to listen. That’s exactly what podcast listeners can experience with adaptive podcasting, a new podcast format that enables producers to make parts of their audio flexible – personalised to each listener, using data from listeners’ devices.

Adaptive podcasting is a key example of object-based media (OBM), an approach to media development pioneered by BBC R&D. OBM puts personalisation at the heart of content creation. By producing media made up of many small, interchangeable assets or objects creators can tell stories that flex and adapt to their respective audiences. Adaptive podcasting is an application of this, envisioning a future where podcasts can be shaped by information about each individual listener, as they are listening.

We envisage that, in the future, adaptive podcasting could be used by all sorts of content creators: sleepcast or children's bedtime story writers making their content adaptable in length, news or information sharers making their content specific to location or knowledge of their listeners. There are so many possibilities for how this technology could benefit podcast listeners' experiences.

Prototype editor on Maker Box

The team worked with freelance developer Rebecca Saw to produce a web-based editor which can create adaptive podcasts, with no coding experience.

The experimental editor provides podcasters with a platform to compile and organise their audio objects, setting various parameters, or switches to control the changes to their content dependent on data available on the listener's device.

The player app

To sit alongside the editor – and to give producers using it somewhere to showcase their podcasts – the team developed a player app, collaborating on this with a series of developers and completed by Manchester-based agency Trunk.

This works by interacting with personal data and sensors on a user's device, as programmed by the podcast creator. As long as the requested data is available and the user has granted permission, the app can then change a podcast's content and length using this information to provide a unique personalised version. As a prototype intended to demonstrate the technology, rather than a finished product, the team decided to release the app as an Early Access application. This means producers and listeners can find it if they have the link to the listing (available on the BBC R&D website).

Keeping data privacy front and centre

The only data accessed on a listener's device will be that which is requested by the particular podcast being played by the listener. For example, if you picked a podcast which varies in length dependent on the time of day, the app would be able to access the time on your device. The app only has access to this data during playback, and that information would never leave your device.

Using a combination of SMIL, JSON, and audio objects means it's not difficult to start building your own podcasts and even host them yourself, completely independently of the BBC.

This is a deliberate position on our part, in keeping with our ethical data principles, and at the same time encouraging the building of a sustainable community of practice beyond our research.

A project centred around collaboration

Open sourcing our code so others can build, extend and even commercialise this approach in OBM without locking anyone out. Everybody gets to play, remix and build.

As the BBC looks to the future of media production, personalisation, and maximising the opportunities that come with such rich data on audiences, Adaptive Podcasting is an exciting experiment into the personalised but ethical data space.

Rebecca Stagg is a project manager working on the BBC’s R&D team. She has led multidisciplinary teams to success for eight years, and has a track record in delivering complex digital projects. Since joining the BBC in 2020, she has delivered a research shoot to support machine learning production exploration, a prototype AR crime scene investigation game app, amongst several audience-focussed tech research projects.