Funded Projects

UKAN+ was awarded funding to coordinate a portfolio of exploratory projects which will accelerate the acoustic community. The funding will support new, ambitious, speculative research spanning the interdisciplinary science of acoustic related research in the UK. The award is to provide funding to address the Acoustics Research Priorities which UKAN+ has identified.

UKAN+ has run two calls to date. Ultimately, in both calls, the best projects were those which were ‘high risk, high reward’ and have potential as the basis or act as a springboard for new, exciting translational research with real industrial application, societal potential or which can lead to large-scale proposals for follow-on research funding.

Call 1

In November 2021 UKAN+ opened our first public call. The award was to provide funding to address the Acoustics Research Priorities which UKAN+ identified. 2 Knowledge Transfers, 2 Network projects and 32 Pilots were awarded.

Acoustic attenuation using advanced nanoporous materials

Project Investigator: Dr Yueting Sun

The group of Dr Yueting Sun at the University of Birmingham teamed up with Dr Jason Raymond and Dr James Kwan at the Oxford Physical Acoustics Laboratory to investigate the potential of using advanced nanoporous materials for acoustic attenuations. Sponge-like materials such as metal-organic frameworks (MOFs) and zeolites offer extremely small pores that are comparable to the size of water molecules. Squeezing liquid water into these tiny nanopores can create large solid-liquid interfaces and dissipate huge amount of mechanical energy. The team will carry out a feasibility study to see how this process can be triggered by acoustic excitations and exploit these materials to attenuate acoustic waves.

Bioacoustic monitoring using drones

Project Investigator: Dr. Lin Wang

Wildlife population monitoring is a major challenge in the context of global biodiversity loss. With the capability of flying over hard-to-reach terrains, drones promise solutions to such monitoring problems. This project conducts pilot research to investigate the potential of using drones for monitoring acoustically active species, such as birds and bats. A major obstacle to address will be the ego-noise generated by the rotating motors and propellers, which leads to extremely low signal-to-noise ratio at airborne microphones if the drone captures wildlife vocalization from a large distance. The project aims to develop a drone audition prototype system for bioacoustic monitoring and address the challenging ego-noise suppression problem. The project has three objectives. 1) To develop a hardware prototype that captures environmental sound with an audio recorder carried by a quadcopter drone; 2) to collect wildlife vocalization dataset with the developed prototype; and 3) to develop wildlife species detection and identification algorithm in the presence of ego-noise.

The project is led by Dr Lin Wang and Dr Axel Rossberg from Queen Mary University of London, and collaborated with Ecology Services Uk Ltd and Bat Conservation Trust.

Developing best-practice guidelines to integrate long-term ecoacoustic methods into UK biodiversity monitoring

Project Investigator: Dr. Oliver Metcalf (ECR)

Co-investigator: Carlos Abrahams (ECR), Director of Bioacoustics at Baker Consultants, and Senior Lecturer at Nottingham Trent University

Biodiversity monitoring is critical to address the climate and biodiversity crises, providing vital information on wildlife populations, shifting distributions, habitat quality and ecosystem functions. Acoustic monitoring facilitates a range of novel methods to make biodiversity monitoring both accurate and cost-effective at large temporal and spatial scales. Within the UK, there is an increasing need to apply these methods of long time periods and in a standardised manner that can be permanently archived, be used in a variety of ways, and that minimises observer biases. However, the opportunity to use these highly effective and cost-saving survey methods is constrained by the lack of good practice guidance for the delivery of ecoacoustic monitoring projects. This Knowledge Transfer Partnership is establishing best practice guidelines for long-term monitoring. It will provide example case studies that illustrate the potential of the methods, and focus firmly on the identified needs from agri-environment, rewilding and BNG - although not be limited to these. The final output of the project will be a published ‘how to’ manual, accessible to practitioners, which provides clear instructions on implementing an ecoacoustic monitoring programme.

Toward a Measure of Soundscape Dynamical Acoustic Complexity using Causal Analysis and AI

Project Investigator: Dr Alice Eldridge

Monitoring, understanding, and predicting the integrity of our planetary biosphere is one of the most critical sustainability issue of our time. The emerging science of Ecoacoustics points to the exciting possibility that eavesdropping on ecosystems may help. The soundscape is a highly dynamic pattern, which emerges from the interaction of the sounds of organisms, physical and technological processes: bees buzzing, birds and bats calling, fish whooping, wind howling, waves crashing and motors throbbing. The soundscape both reflects and influences ecosystem-level behaviours. By analysing soundscape recordings we can predict indicators of ecosystem health such as biodiversity or ecological status. However, current methods analyse short, independent sounds. One can’t appreciate a symphony by listening to isolated fragments; how might we measure the quality of the emergent ecological symphony as a whole?

Call 2

In September 2022 UKAN+ opened our second call. 6 Pilot projects were successful.

An investigation of temporal variability in non-pathological speech: a pilot study towards a robust protocol for remote speech collection for psychological assessment

Project Investigator: Dr Nicholas Cummins, Dr Judith Dineley (ECR)

As acoustic signals, our voices are a valuable window into our mental health. They reflect not only our mood but also the functioning of our brain and its ability to coordinate the 100+ muscles needed to produce speech. Using recordings made on mobile devices, speech analysis could meet the large unmet need for convenient, objective tools that monitor mental health. However, speech analysis is not yet ready for use as a reliable clinical tool in the general population. In this context, how speech is recorded and which metrics to extract for processing are currently neglected steps in analysis pipelines.

Improving our understanding of the natural variability of an individual's voice, that is not caused by illness, and its impact on AI analyses of speech is one aspect that can facilitate translation. For example, could a croaky ‘morning’ voice hide an improvement in our mood? To begin to tackle this, this project has three core objectives: (i) to record healthy volunteers speaking in the morning, afternoon, and evening of a single day; and on three further days at the same time; (ii) to assess the sensitivity of different speech features to variations in individuals’ speech; and (iii) to assess the performance of AI analyses performing depression detection using speech features selected according to their sensitivity to within- and between-day variations in people's voices.

This project is led by Dr Nicholas Cummins and Dr Judith Dineley, Department of Biostatistics and Health Informatics at the Institute of Psychiatry, Psychology & Neuroscience, King’s College London.

Binaural Acoustic Responses in Canines (BARC)

Project Investigator: Project Investigator: Dr Michael McLoughlin

Co-Investigator: Dr Gavin Kearney & Dr Lauren Ward

Assistance dogs carry out a variety of tasks that enable people to lead independent lives. When training for and executing these roles, the dogs rely heavily on spoken word cues from their handlers and learn to react to important sounds in their environment. However, very little is known about how their spatial hearing affects how they carry out these jobs. How well can a guide dog localise sounds associated with danger, such as the sound of oncoming traffic? How difficult is it for a hearing dog to localise the sound of a phone ringing? Further complicating our understanding of dog spatial hearing is the variety of ear shapes and sizes in and between breeds. Recent advances in the study of human spatial hearing use scanned 3D models of human ears to model sound localisation. We will these models and investigate dog spatial hearing by 1) Creating models of dog’s ears using 3D scanners 2) using these 3D scans to generate Head Related Transfer Functions, and 3) determining the accuracy of the models by comparing them to Head Related Transfer Functions collected using traditional methods. We hope to use these models to inform assistance animal training methods.

Characterising spatial freshwater soundscapes on an urban-rural gradient

Project Investigator: Professor Rob Briers, Edinburgh Napier University

Co-I: Dr Alastair Moore, SquareSet Sound

There is significant interest in the potential for measures of freshwater soundscapes to act as a proxy for biodiversity in the same way as has been developed for terrestrial ecosystems. Spatial variability in sound within freshwaters could have a significant influence on the outcome of any assessment and is a key consideration in relation to sampling methods.
Effects of urbanisation such as pollution and differences in habitat may also influence both diversity and identity of sound-producing species in urban and rural ponds. These differences are likely to be reflected in bioacoustic characterisation and may provide an indicator of pressures on the sites.
This project aims to compare existing acoustic sampling methods with a new methodology based on sensor arrays and utilising spatial audio algorithms to examine spatial variability and directionality of sounds. It will also determine the variation in acoustic characteristics of ponds along an urban-rural gradient and the implications of this for acoustic-based biodiversity assessment.

Feasibility of a Marine Acoustic Sensing Network using the UK Archipelago of Offshore Renewable Energy (ORE) Infrastructure

Project Investigator: Dr Anna Young

The UK has an extensive network of offshore renewable energy (ORE) infrastructure for wind and tidal power generation, and this is growing rapidly to meet the ambition of a net-zero future by 2050. Offshore wind power capacity was 11 GW in 2021 (approximately 10% of the UK’s consumption). Tidal power capacity is currently <10 MW but will be expanding by over 400% to 41 MW in the next 5 years with three new or expanding sites in Scotland and Wales. Floating offshore wind has also had its first success in the recent Government Contract for Difference (CfD) auction (32 MW to be installed). These rapid expansions in ORE generation give significant opportunities and challenges for infrastructure design and use. In this project we will explore the potential of multi-purposing the UK's ORE infrastructure to support an extensive underwater acoustic monitoring and surveillance network. Potential applications include monitoring of infrastructure integrity, defence and security of UK waters, biodiversity and population monitoring, underwater navigation and communication, and oceanographic and climate science. The project is led by Dr Anna Young, Dr Phillipe Blondel and Dr Cormac Reale at the University of Bath and we invite collaboration from interested parties.

Patterned ionogel based acoustic sensors (PI-BASe)

Project Investigator: Dr. Andy Reid

The acoustic properties of gels could be game changing if applied to acoustic sensors. Their chemical and material properties can be tailored so that they match the acoustic properties of their environment, such as water, tissue or polymer composites. An acoustic sensor made with this type of material would not be as acoustically intrusive as a rigid ceramic sensor. The large energy loss of a piezoelectric transducer due to the sharp change in acoustic impedance could be avoided, rather than mitigated with coupling gels and matching layers.
This work explores the use of ionogels as acoustic sensors: which are room temperature stable ionic liquids captured in a polymer matrix. Where an ionogel contacts an electrode, a strong interfacial capacitance is formed as the ions from the gel accumulate on the counter charged electrode. This effect is the electrical double layer effect, and creates an extremely high capacitance over a length scale of nanometres. If we exploit this effect by giving the gel a patterned surface, the contact area between the electrode and the gel will change in response to pressure, leading to a rapid change in capacitance and a highly-sensitive impedance-based sensor.

Ultrasonic stimulation and degradation monitoring of electrochemical processes

Project Investigator: Dr. Frederic Cegla

Co-I: Dr. Yifeng Zhang (ECR)
NDE group, Mech Eng., Imperial College London

The net-zero energy transition requires us to shift more and more of our energy generation towards renewable sources for which electrochemical processes are very important. These electrochemical systems are usually diffusion limited and if excessively large charge transfers are imposed degradation in the form of dendrite growth can form. Dendrites are needle like structures that form on the electrode surfaces due to non-uniform ion exchange mechanisms that are driven by the high charge/dis-charge rates. The investigators have already investigated the use of ultrasound to monitor degradation on the electrode surfaces (https://doi.org/10.1016/j.jpowsour.2022.231730) and this project will further investigate if ultrasonic stimulation can enhance diffusion at the electrode/electrolyte interface thus enabling faster charge transfer rates before degradation onset occurs.