Blind source separation and directional audio synthesis for binaural auralization of multiple sound sources using microphone array recordings

2008 ◽  
Author(s):  
Banu Gunel ◽  
Huseyin Hachihabiboglu ◽  
Ahmet Kondoz
Keyword(s):  
Blind Source Separation ◽  
Microphone Array ◽  
Source Separation ◽  
Sound Sources ◽  
Array Recordings

Acoustical feature extraction of rotating machinery with combined wave superposition and blind source separation

2006 ◽  
Vol 220 (9) ◽  
pp. 1423-1431 ◽  
Author(s):  
W F Xue ◽  
J Chen ◽  
J Q Li ◽  
X F Liu
Keyword(s):  
Fault Diagnosis ◽  
Blind Source Separation ◽  
Acoustic Radiation ◽  
Microphone Array ◽  
Source Separation ◽  
Point Sources ◽  
Superposition Method ◽  
Sound Sources ◽  
Reconstruction Process ◽  
Wave Superposition

As the result of vibration emission in air, machine sound signal carries affluent information about the working condition of machine and it can be used to make mechanical fault diagnosis. The fundamental problems with fault diagnosis are the estimation of the number of sound sources and the localization of sound sources. The wave superposition can be employed to identify and locate sound sources, which is based on the idea that an acoustic radiator can be approximated and represented by the sum of the fields due to a finite number of interior point sources. But, in practice, a large number of measurements must be used in order to achieve a desired resolution, which makes the reconstruction process very time-consuming and expensive. In this paper, a combined wave superposition method has been developed reconstruct to acoustic radiation from machine acoustical signals. This method combines the advantages of both the wave superposition and Helmholtz equationleast squares methods, and it allows for reconstruction of the acoustic field from an arbitrary object with relatively few measurements, thus significantly enhancing the reconstruction efficiency. After sound source localization, the blind source separation (BSS) is proposed to extract acoustical feature from the mixed measuring sound signals. In a semi-anechoic chamber, a cross-planar microphone array, which consists of 29 microphones, was successfully applied to obtain the two-dimensional mapping of the sound sources. The location, the sound pressure, and the properties in frequency domain of the sound sources can be found through this method precisely. The experimental results demonstrate that the methods presented can potentially become an acoustical diagnosis tool.

Layout Optimization of Cooperative Distributed Microphone Arrays Based on Estimation of Source Separation Performance

2017 ◽  
Vol 29 (1) ◽  
pp. 83-93
Author(s):  
Kouhei Sekiguchi ◽  
◽  
Yoshiaki Bando ◽  
Katsutoshi Itoyama ◽  
Kazuyoshi Yoshii
Keyword(s):  
Mobile Robots ◽  
Microphone Array ◽  
Source Separation ◽  
Microphone Arrays ◽  
Separation Performance ◽  
Sound Sources ◽  
Multiple Mobile Robots ◽  
Position Information ◽  
Reconfigurable Array ◽  
Source Signals

[abstFig src='/00290001/08.jpg' width='300' text='Optimizing robot positions for source separation' ] The active audition method presented here improves source separation performance by moving multiple mobile robots to optimal positions. One advantage of using multiple mobile robots that each has a microphone array is that each robot can work independently or as part of a big reconfigurable array. To determine optimal layout of the robots, we must be able to predict source separation performance from source position information because actual source signals are unknown and actual separation performance cannot be calculated. Our method thus simulates delay-and-sum beamforming from a possible layout to calculate gain theoretically, i.e., the expected ratio of a target sound source to other sound sources in the corresponding separated signal. Robots are moved into the layout with the highest average gain over target sources. Experimental results showed that our method improved the harmonic mean of signal-to-distortion ratios (SDRs) by 5.5 dB in simulation and by 3.5 dB in a real environment.

scholarly journals Robust Multichannel Microphone Beamforming

2021 ◽  
Author(s):  
◽  
Craig Anderson
Keyword(s):  
Blind Source Separation ◽  
Correlation Functions ◽  
Microphone Array ◽  
Near Field ◽  
Source Separation ◽  
Source Location ◽  
Mobile Platforms ◽  
Signal Path ◽  
Von Mises ◽  
2D And 3D

<p>In this thesis, a method for the design and implementation of a spatially robust multichannel microphone beamforming system is presented.  A set of spatial correlation functions are derived for 2D and 3D far-field/near-field scenarios based on von Mises(-Fisher), Gaussian, and uniform source location distributions. These correlation functions are used to design spatially robust beamformers and blocking beamformers (nullformers) designed to enhance or suppress a known source, where the target source location is not perfectly known due to either an incorrect location estimate or movement of the target while the beamformers are active.  The spatially robust beam/null-formers form signal and interferer plus noise references which can be further processed via a blind source separation algorithm to remove mutual components - removing the interference and sensor noise from the signal path and vice versa. The noise reduction performance of the combined beamforming and blind source separation system approaches that of a perfect information MVDR beamformer under reverberant conditions.  It is demonstrated that the proposed algorithm can be implemented on low-power hardware with good performance on hardware similar to current mobile platforms using a four-element microphone array.</p>

scholarly journals Capturing and Reproducing Spatial Audio Based on a Circular Microphone Array

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Anastasios Alexandridis ◽  
Anthony Griffin ◽  
Athanasios Mouchtaris
Keyword(s):  
Side Information ◽  
Microphone Array ◽  
Audio Signal ◽  
Time Frame ◽  
Spatial Audio ◽  
Sound Sources ◽  
Acoustic Environment ◽  
Listening Tests ◽  
Source Signals ◽  
Array Recordings

This paper proposes a real-time method for capturing and reproducing spatial audio based on a circular microphone array. Following a different approach than other recently proposed array-based methods for spatial audio, the proposed method estimates the directions of arrival of the active sound sources on a per time-frame basis and performs source separation with a fixed superdirective beamformer, which results in more accurate modelling and reproduction of the recorded acoustic environment. The separated source signals are downmixed into one monophonic audio signal, which, along with side information, is transmitted to the reproduction side. Reproduction is possible using either headphones or an arbitrary loudspeaker configuration. The method is compared with other recently proposed array-based spatial audio methods through a series of listening tests for both simulated and real microphone array recordings. Reproduction using both loudspeakers and headphones is considered in the listening tests. As the results indicate, the proposed method achieves excellent spatialization and sound quality.

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