AI-Driven Approaches to Real-Time Spatial Audio for Augmented Reality
Not stated
- Funding
- Self-Funded PhD Students Only
- Application deadline
- Year-round applications
About the project
About the Project The future of Augmented Reality (AR) will be shaped as much by sound as by visuals. For AR to feel truly immersive, virtual sound sources must blend seamlessly with the listener’s real acoustic environment, preserving naturalness, depth, and spatial coherence. Yet this remains a major challenge in immersive media research. Unlike VR, which can operate in fully controlled virtual spaces, AR audio systems must adapt in real time to unknown and dynamic environments. This project will explore novel approaches for estimating and synthesising room acoustics on the fly, enabling AR systems to render sound with convincing distance, direction, and envelopment cues. A key strand of the research will investigate how machine learning techniques can be applied to model sound propagation and acoustic behaviour, ensuring both physical plausibility and computational efficiency. Another critical challenge lies in personalisation. Spatial accuracy depends on individualised binaural filters (HRTFs), but generating these is costly and time-consuming. This project will explore ML-driven methods for adapting generic HRTFs to the individual listener, striking a balance between perceptual accuracy and scalability. Beyond localisation, the work will also focus on maintaining timbral fidelity, ensuring that rendered sound not only “comes from the right place” but also sounds natural and engaging. The project sits at the intersection of spatial audio, acoustics, psychoacoustics, signal processing, and machine learning, offering opportunities to develop new algorithms and frameworks that advance the state of the art in AR audio. Applications span entertainment, gaming, accessibility, telepresence, and simulation training. This project is open at PhD or MSc level, with flexibility to adapt the research focus according to the candidate’s expertise and interests. Entry requirements : Candidates should have (or expect to obtain) a minimum of a UK upper second class honours degree (2.1) or equivalent in Electronic and Electrical Engineering, Physics, Computer Science, Mathematics, Music Technology or a closely related subject. How to apply : Applicants should apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/ . Please read the application guidance first so that you understand the various steps in the application process.