@article{Engel:2023:10.17743/jaes.2022.0066,
author = {Engel, I and Daugintis, R and Vicente, T and Hogg, AOT and Pauwels, J and Tournier, AJ and Picinali, L},
doi = {10.17743/jaes.2022.0066},
journal = {Journal of the Audio Engineering Society},
pages = {241--253},
title = {The SONICOM HRTF dataset},
url = {http://dx.doi.org/10.17743/jaes.2022.0066},
volume = {71},
year = {2023}
}
TY - JOUR
AB - Immersive audio technologies, ranging from rendering spatialized sounds accurately to efficient room simulations, are vital to the success of augmented and virtual realities. To produce realistic sounds through headphones, the human body and head must both be taken into account. However, the measurement of the influence of the external human morphology on the sounds incoming to the ears, which is often referred to as head-related transfer function (HRTF), is expensive and time-consuming. Several datasets have been created over the years to help researcherswork on immersive audio; nevertheless, the number of individuals involved and amount of data collected is often insufficient for modern machine-learning approaches. Here, the SONICOM HRTF dataset is introduced to facilitate reproducible research in immersive audio. This dataset contains the HRTF of 120 subjects, as well as headphone transfer functions; 3D scans of ears, heads, and torsos; and depth pictures at different angles around subjects' heads.
AU - Engel,I
AU - Daugintis,R
AU - Vicente,T
AU - Hogg,AOT
AU - Pauwels,J
AU - Tournier,AJ
AU - Picinali,L
DO - 10.17743/jaes.2022.0066
EP - 253
PY - 2023///
SN - 0004-7554
SP - 241
TI - The SONICOM HRTF dataset
T2 - Journal of the Audio Engineering Society
UR - http://dx.doi.org/10.17743/jaes.2022.0066
UR - https://www.aes.org/e-lib/browse.cfm?elib=22128
UR - http://hdl.handle.net/10044/1/104406
VL - 71
ER -