Machine Learning to Uncover Structure in Bird Vocal Communication

Research Meeting with Dan Stowell (Queen Mary University of London)

We were more than happy to receive this week Dan Stowell, Senior Research Fellow at the Queen Mary University of London, to hear him present his exiting research about bird communication:

Machine learning to uncover structure in bird vocal communication


Animal communication is a topic of scientific importance – and also a significant challenge for data science. We have large amounts of poorly-understood data. Where, in the data, is the structure that will help us to understand animal behaviour?

We describe machine learning methods that we have developed to work with weakly-labelled datasets and structured sequences. We show that applying these to animal sound recordings uncovers patterns of animal behaviour. We will further describe our current work, using neural network embeddings together with animal behavioural studies, to create animal perceptual maps of sound similarity.


Dan Stowell is a Lecturer in machine listening – which means using computation to understand sound signals. He co-leads the Machine Listening Lab at Queen Mary University of London, based in the Centre for Digital Music, and is also a Turing Fellow at the Alan Turing Institute.

Dan has worked on voice, music and environmental soundscapes, and recently led a five-year EPSRC fellowship project researching the automatic analysis of bird sounds. His first degree was from Cambridge University, and his PhD from Queen Mary University of London.

The AI Experience Center

For this edition of our Research Meetings, we invited Dan to speak in our brand new Experience Center. Although not officially open yet, we were happy to be able to take advantage of this beautiful space for this occasion.

The AI Experience Center is currently being developed as a joint project of 4 VUB research groups: the Artificial Intelligence Lab, Brubotics, SMIT and ETRO.

More information will be coming soon!