A Compact Inverse Auditory Model for Binaural Signal Reconstruction

Paul V, Nelson P. A Compact Inverse Auditory Model for Binaural Signal Reconstruction. In: AVARIG 2026: Audio for Virtual and Augmented Reality and Immersive Games. Audio Engineering Society; 2026. Paper 478. Available from: https://aes.org/publications/elibrary-page/?id=23370

@inproceedings{Paul2026_23370,
  author = {Paul, Vlad and Nelson, Philip},
  title = {{A Compact Inverse Auditory Model for Binaural Signal Reconstruction}},
  booktitle = {AVARIG 2026: Audio for Virtual and Augmented Reality and Immersive Games},
  note = {Paper 478},
  year = {2026},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=23370}
}

TY  - CPAPER
TI  - A Compact Inverse Auditory Model for Binaural Signal Reconstruction
AU  - Paul, Vlad
AU  - Nelson, Philip
T2  - AVARIG 2026: Audio for Virtual and Augmented Reality and Immersive Games
M1  - Paper 478
PY  - 2026
DA  - 2026/06/30
UR  - https://aes.org/publications/elibrary-page/?id=23370
PB  - Audio Engineering Society
LA  - en
AB  - Binaural signal synthesis is typically formulated as forward modelling using head-related transfer functions (HRTFs). We explore an inverse auditory modelling perspective in which binaural ear signals are estimated directly from a source signal and its azimuth. We present a lightweight complex-valued neural network that predicts frequency-domain binaural filters from the input source spectrum and azimuthal direction, which are then applied to synthesize binaural signals. Controlled experiments evaluate how excitation bandwidth and angular sampling density affect reconstruction and generalization. Results show accurate spectral reconstruction and interpolation to unseen source directions even when training uses sparse angular grids, while bandwidth strongly influences problem conditioning and error behaviour. This work focuses on
ER  -