Making sense of sounds
The aim of this project is to investigate, develop and demonstrate new ways to make sense from large amounts of everyday sounds, focussing on real-world non-music, non-speech sounds and soundscapes.
In this way, we will realize latent value in existing sound and broadcast archives, enable more productive interaction with sound data, and improve the lives of people in their sound environment.
To achieve this aim, our specific objectives are:
1. To investigate and develop new machine learning and signal processing methods to analyse sounds and soundscapes.
2. To investigate how to use other modalities such as vision and text that can bring complementary information to improve analysis and interaction with sound-focussed data.
3. To investigate human sound perception and cognition in the context of sound data understanding, including emotional response, attention and context.
4. To build a research software framework and datasets to encourage other researchers to contribute to the field; and to build a set of software demonstrators to illustrate the outcomes to potential users.
5. To create a network of national and international partners from academia and industry, to realize the potential of current and future research and applications in making sense of sound data.
The project team includes staff at the Universities of Surrey and Salford. The Surrey staff are Mark Plumbley (PI), Philip Jackson, David Frohlich, Wenwu Wang, Christian Kroos, Yong Xu, Qiuqiang Kong, Qiang Huang & Iwona Sobieraj. The Salford staff are Bill Davies, Trevor Cox and Oliver Bones. The project is funded by a grant of £1.59m from the EPSRC Making sense of data programme (EP/N014111/1), and runs from 1.1.16 for 36 months.
Further details are on the main project website.