Spherical Microphone Array Beamforming

2010 ◽  
pp. 281-305 ◽  
Author(s):  
Boaz Rafaely ◽  
Yotam Peled ◽  
Morag Agmon ◽  
Dima Khaykin ◽  
Etan Fisher
Keyword(s):  
Microphone Array ◽  
Array Beamforming

Circular microphone array beamforming to improve speech recognition for virtual agents

2021 ◽  
Vol 150 (4) ◽  
pp. A172-A172
Author(s):  
Gary W. Elko ◽  
Jens Meyer ◽  
Heinz Teutsch ◽  
Tomas Gaensler
Keyword(s):  
Speech Recognition ◽  
Microphone Array ◽  
Virtual Agents ◽  
Array Beamforming

Using spherical microphone array beamforming and Bayesian inference to evaluate room acoustics

2012 ◽  
Vol 132 (3) ◽  
pp. 2058-2058
Author(s):  
Samuel Clapp ◽  
Jonathan Botts ◽  
Anne Guthrie ◽  
Ning Xiang ◽  
Jonas Braasch
Keyword(s):  
Bayesian Inference ◽  
Microphone Array ◽  
Room Acoustics ◽  
Array Beamforming

scholarly journals Ad hoc microphone array beamforming using the primal-dual method of multipliers

2016 ◽  
Author(s):  
Vincent M. Tavakoli ◽  
Jesper R. Jensen ◽  
Richard Heusdens ◽  
Jacob Benesty ◽  
Mads G. Christensen
Keyword(s):  
Ad Hoc ◽  
Microphone Array ◽  
Dual Method ◽  
Method Of Multipliers ◽  
Primal Dual ◽  
Array Beamforming

scholarly journals Classification, positioning, and tracking of drones by HMM using acoustic circular microphone array beamforming

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Junfeng Guo ◽  
Ishtiaq Ahmad ◽  
KyungHi Chang
Keyword(s):  
Background Noise ◽  
Microphone Array ◽  
Reference Signal ◽  
Adaptive Beamforming ◽  
Commercial Application ◽  
Monitoring Systems ◽  
Focal Points ◽  
Sound Sources ◽  
Recorded Sound ◽  
Array Beamforming

AbstractThis paper addresses issues with monitoring systems that identify and track illegal drones. The development of drone technologies promotes the widespread commercial application of drones. However, the ability of a drone to carry explosives and other destructive materials may pose serious threats to public safety. In order to reduce these threats, we propose an acoustic-based scheme for positioning and tracking of illegal drones. Our proposed scheme has three main focal points. First, we scan the sky with switched beamforming to find sound sources and record the sounds using a microphone array; second, we perform classification with a hidden Markov model (HMM) in order to know whether the sound is a drone or something else. Finally, if the sound source is a drone, we use its recorded sound as a reference signal for tracking based on adaptive beamforming. Simulations are conducted under both ideal conditions (without background noise and interference sounds) and non-ideal conditions (with background noise and interference sounds), and we evaluate the performance when tracking illegal drones.

Sign in / Sign up

Export Citation Format

Share Document