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One of the biggest challenges for the BBC Archive is how to open up our enormous collection of radio programmes. As we’ve been broadcasting since 1922 we’ve got an archive of almost 100 years of audio recordings, representing a unique cultural and historical resource.
But the big problem is how to make it searchable. Many of the programmes have little or no meta-data, and the whole collection is far too large to process through human efforts alone.
Help is at hand. Over the last five years or so, technologies such as automated speech recognition, speaker identification and automated tagging have reached a level of accuracy where we can start to get impressive results for the right type of audio. By automatically analysing sound files and making informed decisions about the content and speakers, these tools can effectively help to fill in the missing gaps in our archive’s meta-data.
BBC R&D decided to develop these automatic meta-data extraction technologies in a way that would allow large-scale audio processing. Building them into a cloud-based platform (more on this later) allows us to work through very large archives quickly, cheaply and many times over.
