Basant Pandagre
ABSTRACT
Spatial audio rendering employs Head Related Transfer Functions (HRTFs) for a realistic reproduction of the sound field. This requires upsampling of the HRTF. Given its popularity for the task of upsampling, a deep learning (DL) based upsampler can appear to be an attractive solution for the said problem. We, however, argue that it is more meaningful to rely on explicit system modeling, and not depend exclusively on DL based data fitting for the said problem.
- Corey I Cheng and Gregory H Wakefield. 2001. introduction to head-related transfer functions (hrtfs): representations of hrtfs in time, frequency, and space. journal of the audio engineering society 49, 4 (april 2001), 231–249.Google Scholar
- Grady Kestler, Shahrokh Yadegari, and David Nahamoo. 2019. Head related impulse response interpolation and extrapolation using Deep Belief Networks. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, Brighton, UK, 266–270.Google ScholarCross Ref
- Devansh Zurale, Shahrokh Yadegari, and Shlomo Dubnov. 2022. Deep HRTF Encoding & Interpolation: Exploring Spatial Correlations using Convolutional Neural Networks. In "". Zenodo, Saint-Etienne (France) Zenodo, 350–357.Google Scholar
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