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.

scholarly journals Creation of Auditory Augmented Reality Using a Position-Dynamic Binaural Synthesis System—Technical Components, Psychoacoustic Needs, and Perceptual Evaluation

2021 ◽  
Vol 11 (3) ◽  
pp. 1150
Author(s):  
Stephan Werner ◽  
Florian Klein ◽  
Annika Neidhardt ◽  
Ulrike Sloma ◽  
Christian Schneiderwind ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Auditory Perception ◽  
Audio Signal ◽  
Spatial Audio ◽  
Impulse Responses ◽  
Synthesis System ◽  
Perceptual Evaluation ◽  
Listening Tests ◽  
Work Done ◽  
Audio Reproduction

For a spatial audio reproduction in the context of augmented reality, a position-dynamic binaural synthesis system can be used to synthesize the ear signals for a moving listener. The goal is the fusion of the auditory perception of the virtual audio objects with the real listening environment. Such a system has several components, each of which help to enable a plausible auditory simulation. For each possible position of the listener in the room, a set of binaural room impulse responses (BRIRs) congruent with the expected auditory environment is required to avoid room divergence effects. Adequate and efficient approaches are methods to synthesize new BRIRs using very few measurements of the listening room. The required spatial resolution of the BRIR positions can be estimated by spatial auditory perception thresholds. Retrieving and processing the tracking data of the listener’s head-pose and position as well as convolving BRIRs with an audio signal needs to be done in real-time. This contribution presents work done by the authors including several technical components of such a system in detail. It shows how the single components are affected by psychoacoustics. Furthermore, the paper also discusses the perceptive effect by means of listening tests demonstrating the appropriateness of the approaches.

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.

Localisation of Sound Sources on Aircraft in Flight

2012 ◽  
Author(s):  
Henri A. Siller
Keyword(s):  
Dynamic Range ◽  
Microphone Array ◽  
Acoustic Power ◽  
Microphone Arrays ◽  
Sound Sources ◽  
Noise Abatement ◽  
Source Regions ◽  
The Time Domain ◽  
Imaging Properties ◽  
Source Signals

This paper presents beamforming techniques for source localization on aicraft in flight with a focus on the development at DLR in Germany. Fly-over tests with phased arrays are the only way to localize and analyze the different aerodynamic and engine sources of aircraft in flight. Many of these sources cannot be simulated numerically or in wind-tunnel tests because they they are either unknown or they cannot be resolved properly in model scale. The localization of sound sources on aircraft in flight is performed using large microphone arrays. For the data analysis, the source signals at emission time are reconstructed from the Doppler-shifted microphone data using the measured flight trajectory. Standard beamforming techniques in the frequency domain cannot be applied due transitory nature of the signals, so the data is usually analyzed using a classical beamforming algorithm in the time domain. The spatial resolution and the dynamic range of the source maps can be improved by calculating a deconvolution of the sound source maps with the point spread function of the microphone array. This compensates the imaging properties of the microphone array by eliminating side lobes and aliases. While classical beamfoming yields results that are more qualitative by nature, the deconvolution results can be used to integrate the acoustic power over the different source regions in order to obtain the powers of each source. ranking of the sources. These results can be used to rank the sources, for acoustic trouble shooting, and to assess the potential of noise abatement methods.

Parametric Spatial Audio Processing of Spaced Microphone Array Recordings for Multichannel Reproduction

2015 ◽  
Vol 63 (4) ◽  
pp. 216-227 ◽  
Author(s):  
Archontis Politis ◽  
Mikko-Ville Laitinen ◽  
Jukka Ahonen ◽  
Ville Pulkki
Keyword(s):  
Microphone Array ◽  
Spatial Audio ◽  
Audio Processing ◽  
Array Recordings

An ICA-Based Audio Feature Fault Detection Method for Transformer Equipments

2013 ◽  
Vol 805-806 ◽  
pp. 706-711 ◽  
Author(s):  
Shi Bin Du ◽  
Guan Yu Tian ◽  
Shu Zhong Bai ◽  
Lan Tian
Keyword(s):  
Signal Processing ◽  
Fault Detection ◽  
Detection System ◽  
Microphone Array ◽  
Audio Signal ◽  
Electrical Equipment ◽  
System Structure ◽  
Audio Signal Processing ◽  
Independent Source ◽  
Source Signals

Experienced engineers in transformer substation can judge the equipment condition via just listening to the working sounds of electrical equipments. Use audio signal processing applied in engines and other mechanical equipments for reference. A scheme to monitor the working condition of electrical equipments is proposed. Firstly, the basic principles and system structure of this scheme is outlined. It introduces the method of colleting electrical equipments working sounds by Microphone array, because Microphone array form a beam to target the source sound, which can reduce the noise and reverberation. When substation is working, the environmental background interference sounds exist and are independent from electrical working sound. So we can use FastICA algorithm that is based on the largest negentropy to separate the collected sound to several independent source signals. It has the advantage of fast convergence and robust. The simulation result shows this algorithm can effectively separate the multiple independent source signals. The separation accuracy is above 95% for typical sample mixed sounds and the reliability of electrical equipment fault detection system based on audio signal processing is ensured.

scholarly journals Stochastic Restoration of Heavily Compressed Musical Audio Using Generative Adversarial Networks

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1349
Author(s):  
Stefan Lattner ◽  
Javier Nistal
Keyword(s):  
Data Storage ◽  
Audio Signal ◽  
Human Perception ◽  
Generative Adversarial Networks ◽  
Audio Signals ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Extensive Evaluation ◽  
Listening Tests ◽  
Musical Audio

Lossy audio codecs compress (and decompress) digital audio streams by removing information that tends to be inaudible in human perception. Under high compression rates, such codecs may introduce a variety of impairments in the audio signal. Many works have tackled the problem of audio enhancement and compression artifact removal using deep-learning techniques. However, only a few works tackle the restoration of heavily compressed audio signals in the musical domain. In such a scenario, there is no unique solution for the restoration of the original signal. Therefore, in this study, we test a stochastic generator of a Generative Adversarial Network (GAN) architecture for this task. Such a stochastic generator, conditioned on highly compressed musical audio signals, could one day generate outputs indistinguishable from high-quality releases. Therefore, the present study may yield insights into more efficient musical data storage and transmission. We train stochastic and deterministic generators on MP3-compressed audio signals with 16, 32, and 64 kbit/s. We perform an extensive evaluation of the different experiments utilizing objective metrics and listening tests. We find that the models can improve the quality of the audio signals over the MP3 versions for 16 and 32 kbit/s and that the stochastic generators are capable of generating outputs that are closer to the original signals than those of the deterministic generators.

scholarly journals Spatial accuracy of binaural synthesis from rigid spherical microphone array recordings

2017 ◽  
Vol 38 (1) ◽  
pp. 23-30 ◽  
Author(s):  
César D. Salvador ◽  
Shuichi Sakamoto ◽  
Jorge Treviño ◽  
Yôiti Suzuki
Keyword(s):  
Microphone Array ◽  
Spatial Accuracy ◽  
Array Recordings
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