Sound Source Localization
38 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Sound Source Localization
Most implemented papers
Differentiable Tracking-Based Training of Deep Learning Sound Source Localizers
Data-based and learning-based sound source localization (SSL) has shown promising results in challenging conditions, and is commonly set as a classification or a regression problem.
Iterative Sound Source Localization for Unknown Number of Sources
Sound source localization aims to seek the direction of arrival (DOA) of all sound sources from the observed multi-channel audio.
Deep Neural Networks for Multiple Speaker Detection and Localization
deepspike/Binary-Neural-Network-for-Sound-Localization
•
•
We propose to use neural networks for simultaneous detection and localization of multiple sound sources in human-robot interaction.
Audio-Visual Scene Analysis with Self-Supervised Multisensory Features
andrewowens/multisensory
•
•
ECCV 2018
The thud of a bouncing ball, the onset of speech as lips open -- when visual and audio events occur together, it suggests that there might be a common, underlying event that produced both signals.
Direction of Arrival with One Microphone, a few LEGOs, and Non-Negative Matrix Factorization
Monaural localization is possible thanks to the scattering by the head, though it hinges on learning the spectra of the various sources.
The LOCATA Challenge: Acoustic Source Localization and Tracking
The aim of the LOCAlization and TrAcking (LOCATA) Challenge is an open-access framework for the objective evaluation and benchmarking of broad classes of algorithms for sound source localization and tracking.
Learning to Localize Sound Sources in Visual Scenes: Analysis and Applications
ardasnck/learning_to_localize_sound_source
•
•
Visual events are usually accompanied by sounds in our daily lives.
DOANet: a deep dilated convolutional neural network approach for search and rescue with drone-embedded sound source localization
DOANet is based on a one-dimensional dilated convolutional neural network that computes the azimuth and elevation angles of the target sound source from the raw audio signal.
Localize to Binauralize: Audio Spatialization From Visual Sound Source Localization
Through user study, we further validate that our proposed approach generates binaural-quality audio using as little as 10% of explicit binaural supervision data for the SG network.
ODAS: Open embeddeD Audition System
Artificial audition aims at providing hearing capabilities to machines, computers and robots.
