A self-supervised model learns acoustic maps from unlabeled microphone data and performs direction-of-arrival estimation on par with supervised methods.
Multiple emitter location and signal parameter estimation,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.SD 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Latent Acoustic Mapping for Direction of Arrival Estimation: A Self-Supervised Approach
A self-supervised model learns acoustic maps from unlabeled microphone data and performs direction-of-arrival estimation on par with supervised methods.