Use of acoustic filtering to control the beamwidth of steered microphone arrays

1985 ◽  
Vol 77 (S1) ◽  
pp. S16-S16
Author(s):  
J. L. Flanagan
Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3446
Author(s):  
Muhammad Usman Liaquat ◽  
Hafiz Suliman Munawar ◽  
Amna Rahman ◽  
Zakria Qadir ◽  
Abbas Z. Kouzani ◽  
...  

Sound localization is a field of signal processing that deals with identifying the origin of a detected sound signal. This involves determining the direction and distance of the source of the sound. Some useful applications of this phenomenon exists in speech enhancement, communication, radars and in the medical field as well. The experimental arrangement requires the use of microphone arrays which record the sound signal. Some methods involve using ad-hoc arrays of microphones because of their demonstrated advantages over other arrays. In this research project, the existing sound localization methods have been explored to analyze the advantages and disadvantages of each method. A novel sound localization routine has been formulated which uses both the direction of arrival (DOA) of the sound signal along with the location estimation in three-dimensional space to precisely locate a sound source. The experimental arrangement consists of four microphones and a single sound source. Previously, sound source has been localized using six or more microphones. The precision of sound localization has been demonstrated to increase with the use of more microphones. In this research, however, we minimized the use of microphones to reduce the complexity of the algorithm and the computation time as well. The method results in novelty in the field of sound source localization by using less resources and providing results that are at par with the more complex methods requiring more microphones and additional tools to locate the sound source. The average accuracy of the system is found to be 96.77% with an error factor of 3.8%.


2021 ◽  
Vol 11 (11) ◽  
pp. 4829
Author(s):  
Vojtech Chmelík ◽  
Daniel Urbán ◽  
Lukáš Zelem ◽  
Monika Rychtáriková

In this paper, with the aim of assessing the deterioration of speech intelligibility caused by a speaker wearing a mask, different face masks (surgical masks, FFP2 mask, homemade textile-based protection and two kinds of plastic shields) are compared in terms of their acoustic filtering effect, measured by placing the mask on an artificial head/mouth simulator. For investigating the additional effects on the speaker’s vocal output, speech was also recorded while people were reading a text when wearing a mask, and without a mask. In order to discriminate between effects of acoustic filtering by the mask and mask-induced effects of vocal output changes, the latter was monitored by measuring vibrations at the suprasternal notch, using an attached accelerometer. It was found that when wearing a mask, people tend to slightly increase their voice level, while when wearing plastic face shield, they reduce their vocal power. Unlike the Lombard effect, no significant change was found in the spectral content. All face mask and face shields attenuate frequencies above 1–2 kHz. In addition, plastic shields also increase frequency components to around 800 Hz, due to resonances occurring between the face and the shield. Finally, special attention was given to the Slavic languages, in particular Slovak, which contain a large variety of sibilants. Male and female speech, as well as texts with and without sibilants, was compared.


2019 ◽  
Vol 283 ◽  
pp. 04001
Author(s):  
Boquan Yang ◽  
Shengguo Shi ◽  
Desen Yang

Recently, spherical microphone arrays (SMA) have become increasingly significant for source localization and identification in three dimension due to its spherical symmetry. However, conventional Spherical Harmonic Beamforming (SHB) based on SMA has limitations, such as poor resolution and high side-lobe levels in image maps. To overcome these limitations, this paper employs the iterative generalized inverse beamforming algorithm with a virtual extrapolated open spherical microphone array. The sidelobes can be suppressed and the main-lobe can be narrowed by introducing the two iteration processes into the generalized inverse beamforming (GIB) algorithm. The instability caused by uncertainties in actual measurements, such as measurement noise and configuration problems in the process of GIB, can be minimized by iteratively redefining the form of regularization matrix and the corresponding GIB localization results. In addition, the poor performance of microphone arrays in the low-frequency range due to the array aperture can be improved by using a virtual extrapolated open spherical array (EA), which has a larger array aperture. The virtual array is obtained by a kind of data preprocessing method through the regularization matrix algorithm. Both results from simulations and experiments show the feasibility and accuracy of the method.


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