Name
Title | ||
|---|---|---|
CRNN-Based Multiple DoA Estimation Using Acoustic Intensity Features for Ambisonics Recordings. |
Abstract | ||
|---|---|---|
Localizing audio sources is challenging in real reverberant environments, especially when several sources are active. We propose to use a neural network built from stacked convolutional and recurrent layers in order to estimate the directions of arrival of multiple sources from a first-order Ambisonics recording. It returns the directions of arrival over a discrete grid of a known number of source... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JSTSP.2019.2900164 | IEEE Journal of Selected Topics in Signal Processing |
Keywords | Field | DocType |
Direction-of-arrival estimation,Estimation,Neural networks,Microphones,Convolution,Acoustics,Time-frequency analysis | Computer vision,Visualization,Convolution,Direction of arrival,Computer science,Ambisonics,Time–frequency analysis,Artificial intelligence,Artificial neural network,Sound intensity,Grid | Journal |
Volume | Issue | ISSN |
13 | 1 | 1932-4553 |
Citations | PageRank | References |
13 | 0.65 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laureline Perotin | 1 | 15 | 1.04 |
| Romain Serizel | 2 | 118 | 13.05 |
| Emmanuel Vincent | 3 | 2963 | 186.26 |
| Alexandre Guérin | 4 | 13 | 0.99 |