Immersive Audio and Network Music Performance Dataset
This dataset contains supplementary materials for a doctoral thesis exploring immersive audio and networked musical collaboration. The dataset includes anonymised Quality of Experience (QoE) rating data and technical analyses across four chapters covering different aspects of immersive network music performance (INMP).
Description
This dataset contains supplementary materials for a doctoral thesis exploring immersive audio and networked musical collaboration. The dataset includes anonymised Quality of Experience (QoE) rating data and technical analyses across four chapters covering different aspects of immersive network music performance (INMP).
The materials include head-related impulse responses (BRIR) for audio auralization, subjective quality ratings, tempo analysis with audio files and MATLAB scripts, synchrony measurements, spatial impulse responses (SRIR), onset timing data, and comprehensive statistical analyses. The research examines the viability of immersive network music performance use-cases and explores virtual acoustic methods, particularly Ambisonic and binaural audio approaches.
The research was funded by EP/X525856/1 and a University of York studentship, with related publications including work on metaverse music performance with BBC Maida Vale Recording Studios.
Access
Restricted files. Record is publicly accessible, but file access is limited to authorized users. Contact the dataset creator through Zenodo for access.