scholarly journals Study on 3D Sound Source Visualization Using Frequency Domain Beamforming Method

2009 ◽  
Vol 19 (9) ◽  
pp. 907-914
Keyword(s):  
Frequency Domain ◽  
Sound Source ◽  
3D Sound

It's only real if you see it: Surround system based 3D sound source modelling in virtual reality

2013 ◽  
Author(s):  
Agoston Torok ◽  
Daniel Mestre ◽  
Ferenc Honbolygo ◽  
Pierre Mallet ◽  
Jean-Marie Pergandi ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Sound Source ◽  
3D Sound

Combining SRP-PHAT and two Kinects for 3D Sound Source Localization

2014 ◽  
Vol 41 (16) ◽  
pp. 7106-7113 ◽  
Author(s):  
Lucas Adams Seewald ◽  
Luiz Gonzaga ◽  
Mauricio Roberto Veronez ◽  
Vicente Peruffo Minotto ◽  
Cláudio Rosito Jung
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Sound Source Localization ◽  
3D Sound

Study of 3D Sound of Airport Crash Fire Vehicle Simulator

2011 ◽  
Vol 105-107 ◽  
pp. 2221-2224
Author(s):  
Li Wen Wang ◽  
Dan Dan Shi ◽  
Hao Wang
Keyword(s):  
Sound Source ◽  
Physical Structure ◽  
Sound System ◽  
3D Sound ◽  
Training Cost ◽  
Vehicle Simulator ◽  
Head Related Transfer Function ◽  
Voice Message ◽  
Listening Experiment ◽  
The Impact

Airport crash fire vehicle simulator is an important device that is used in training of the airport firefighters, which has advantage of safe, energy saving and decreasing training cost. Sound system is an important part of airport crash fire vehicle simulator, which provides voice message to training personnel, which can make training personnel have immersed sense. Based on the principles of sound source position to analyze the different physical structure of the human body (head, torso, pinna) the impact of sound localization, the establishment of head-related transfer function model, using the model of the sound source, filtering, delay processing, and virtual sound source. And we have tested and verified with listening experiment.

scholarly journals A multichannel learning-based approach for sound source separation in reverberant environments

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
You-Siang Chen ◽  
Zi-Jie Lin ◽  
Mingsian R. Bai
Keyword(s):  
Frequency Domain ◽  
Sound Source ◽  
Signal To Noise Ratio ◽  
Source Separation ◽  
Objective Evaluation ◽  
Linear Mapping ◽  
Invariant Mean ◽  
Scale Invariant ◽  
Sound Source Separation ◽  
Reverberant Field

AbstractIn this paper, a multichannel learning-based network is proposed for sound source separation in reverberant field. The network can be divided into two parts according to the training strategies. In the first stage, time-dilated convolutional blocks are trained to estimate the array weights for beamforming the multichannel microphone signals. Next, the output of the network is processed by a weight-and-sum operation that is reformulated to handle real-valued data in the frequency domain. In the second stage, a U-net model is concatenated to the beamforming network to serve as a non-linear mapping filter for joint separation and dereverberation. The scale invariant mean square error (SI-MSE) that is a frequency-domain modification from the scale invariant signal-to-noise ratio (SI-SNR) is used as the objective function for training. Furthermore, the combined network is also trained with the speech segments filtered by a great variety of room impulse responses. Simulations are conducted for comprehensive multisource scenarios of various subtending angles of sources and reverberation times. The proposed network is compared with several baseline approaches in terms of objective evaluation matrices. The results have demonstrated the excellent performance of the proposed network in dereverberation and separation, as compared to baseline methods.

Binaural Source Localization and Spatial Audio Reproduction for Telepresence Applications

2007 ◽  
Vol 16 (5) ◽  
pp. 509-522 ◽  
Author(s):  
Fakheredine Keyrouz ◽  
Klaus Diepold
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Transfer Functions ◽  
Superior Performance ◽  
High Fidelity ◽  
Spatial Audio ◽  
3D Sound ◽  
Perceptual Presence ◽  
Remote Environment ◽  
Audio Reproduction

Telepresence is generally described as the feeling of being immersed in a remote environment, be it virtual or real. A multimodal telepresence environment, equipped with modalities such as vision, audition, and haptic, improves immersion and augments the overall perceptual presence. The present work focuses on acoustic telepresence at both the teleoperator and operator sites. On the teleoperator side, we build a novel binaural sound source localizer using generic Head Related Transfer Functions (HRTFs). This new localizer provides estimates for the direction of a single sound source given in terms of azimuth and elevation angles in free space by using only two microphones. It also uses an algorithm that is efficient compared to the currently known algorithms used in similar localization processes. On the operator side, the paper addresses the problem of spatially interpolating HRTFs for densely sampled high-fidelity 3D sound synthesis. In our telepresence application scenario the synthesized 3D sound is presented to the operator over headphones and shall achieve a high-fidelity acoustic immersion. Using measured HRTF data, we create interpolated HRTFs between the existing functions using a matrix-valued interpolation function. The comparison with existing interpolation methods reveals that our new method offers superior performance and is capable of achieving high-fidelity reconstructions of HRTFs.

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