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A machine learning tutorial for spatial auditory display using head-related transfer functions.
- Source :
- Journal of the Acoustical Society of America; Feb2022, Vol. 151 Issue 2, p1277-1293, 17p
- Publication Year :
- 2022
-
Abstract
- This review presents a high-level overview of the uses of machine learning (ML) to address several challenges in spatial auditory display research, primarily using head-related transfer functions. This survey also reviews and compares several categories of ML techniques and their application to virtual auditory reality research. This work addresses the use of ML techniques such as dimensionality reduction, unsupervised learning, supervised learning, reinforcement learning, and deep learning algorithms. The paper concludes with a discussion of the usage of ML algorithms to address specific spatial auditory display research challenges. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00014966
- Volume :
- 151
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Journal of the Acoustical Society of America
- Publication Type :
- Academic Journal
- Accession number :
- 155493109
- Full Text :
- https://doi.org/10.1121/10.0007486