scholarly journals Assessment of Sound Source Tracking Using Multiple Drones Equipped with Multiple Microphone Arrays

2021 ◽  
Vol 18 (17) ◽  
pp. 9039
Author(s):  
Taiki Yamada ◽  
Katsutoshi Itoyama ◽  
Kenji Nishida ◽  
Kazuhiro Nakadai
Keyword(s):  
Numerical Simulation ◽  
Performance Assessment ◽  
Sound Source ◽  
Microphone Arrays ◽  
Source Tracking ◽  
Signal To Noise ◽  
Sound Sources ◽  
Tracking Method ◽  
Low Snr ◽  
Source Distance

Drone audition techniques are helpful for listening to target sound sources from the sky, which can be used for human searching tasks in disaster sites. Among many techniques required for drone audition, sound source tracking is an essential technique, and thus several tracking methods have been proposed. Authors have also proposed a sound source tracking method that utilizes multiple microphone arrays to obtain the likelihood distribution of the sound source locations. These methods have been demonstrated in benchmark experiments. However, the performance against various sound sources with different distances and signal-to-noise ratios (SNRs) has been less evaluated. Since drone audition often needs to listen to distant sound sources and the input acoustic signal generally has a low SNR due to drone noise, making a performance assessment against source distance and SNR is essential. Therefore, this paper presents a concrete evaluation of sound source tracking methods using numerical simulation, focusing on various source distances and SNRs. The simulated results captured how the tracking performance will change when the sound source distance and SNR change. The proposed approach based on location distribution estimation tended to be more robust against distance increase, while existing approaches based on directional estimation tended to be more robust against decreasing SNR.

Asynchronous microphone arrays calibration and sound source tracking

2019 ◽  
Vol 44 (2) ◽  
pp. 183-204 ◽  
Author(s):  
Daobilige Su ◽  
Teresa Vidal-Calleja ◽  
Jaime Valls Miro
Keyword(s):  
Sound Source ◽  
Microphone Arrays ◽  
Source Tracking

scholarly journals Compressing Sensing Based Source Localization for Controlled Acoustic Signals Using Distributed Microphone Arrays

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Wei Ke ◽  
Xiunan Zhang ◽  
Yanan Yuan ◽  
Jianhua Shao
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Reconstruction Algorithm ◽  
Acoustic Signals ◽  
Substantial Improvement ◽  
Microphone Arrays ◽  
Sound Source Localization ◽  
Sound Sources ◽  
Reconstruction Performance ◽  
Long Time

In order to enhance the accuracy of sound source localization in noisy and reverberant environments, this paper proposes an adaptive sound source localization method based on distributed microphone arrays. Since sound sources lie at a few points in the discrete spatial domain, our method can exploit this inherent sparsity to convert the localization problem into a sparse recovery problem based on the compressive sensing (CS) theory. In this method, a two-step discrete cosine transform- (DCT-) based feature extraction approach is utilized to cover both short-time and long-time properties of acoustic signals and reduce the dimensions of the sparse model. In addition, an online dictionary learning (DL) method is used to adjust the dictionary for matching the changes of audio signals, and then the sparse solution could better represent location estimations. Moreover, we propose an improved block-sparse reconstruction algorithm using approximate l0 norm minimization to enhance reconstruction performance for sparse signals in low signal-noise ratio (SNR) conditions. The effectiveness of the proposed scheme is demonstrated by simulation results and experimental results where substantial improvement for localization performance can be obtained in the noisy and reverberant conditions.

Sound Source Tracking by Drones with Microphone Arrays

2020 ◽  
Author(s):  
Taiki Yamada ◽  
Katsutoshi Itoyama ◽  
Kenji Nishida ◽  
Kazuhiro Nakadai
Keyword(s):  
Sound Source ◽  
Microphone Arrays ◽  
Source Tracking

scholarly journals DATASET FOR EVALUATION OF THE PERFORMANCE OF THE METHODS OF SOUND SOURCE LOCALIZATION ALGORITHMS USING TETRAHEDRAL MICROPHONE ARRAYS

2020 ◽  
Vol 12 (0) ◽  
pp. 1-8
Author(s):  
Saulius Sakavičius
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Microphone Array ◽  
Direction Of Arrival ◽  
Microphone Arrays ◽  
Sound Source Localization ◽  
Direction Of Arrival Estimation ◽  
Sound Sources ◽  
Localization Algorithms ◽  
Geometrical Information

For the development and evaluation of a sound source localization and separation methods, a concise audio dataset with complete geometrical information about the room, the positions of the sound sources, and the array of microphones is needed. Computer simulation of such audio and geometrical data often relies on simplifications and are sufficiently accurate only for a specific set of conditions. It is generally desired to evaluate algorithms on real-world data. For a three-dimensional sound source localization or direction of arrival estimation, a non-coplanar microphone array is needed.Simplest and most general type of non-coplanar array is a tetrahedral array. There is a lack of openly accessible realworld audio datasets obtained using such arrays. We present an audio dataset for the evaluation of sound source localization algorithms, which involve tetrahedral microphone arrays. The dataset is complete with the geometrical information of the room, the positions of the sound sources and the microphone array. Array audio data was captured for two tetrahedral microphone arrays with different distances between microphones and one or two active sound sources. The dataset is suitable for speech recognition and direction-of-arrival estimation, as the signals used for sound sources were speech signals.

Role of pinnae and head movements in localizing pure tones 1The authors would like to thank Mr. Remi Humbert for implementing the experiment in Turbo Pascal and for his further assistance.

1999 ◽  
Vol 58 (3) ◽  
pp. 170-179 ◽  
Author(s):  
Barbara S. Muller ◽  
Pierre Bovet
Keyword(s):  
Sound Source ◽  
Head Movement ◽  
Movement Analysis ◽  
Head Movements ◽  
Sound Sources ◽  
Localization Accuracy ◽  
Sound Effects ◽  
Posterior Quadrant ◽  
Localization Performance ◽  
Pure Tones

Twelve blindfolded subjects localized two different pure tones, randomly played by eight sound sources in the horizontal plane. Either subjects could get information supplied by their pinnae (external ear) and their head movements or not. We found that pinnae, as well as head movements, had a marked influence on auditory localization performance with this type of sound. Effects of pinnae and head movements seemed to be additive; the absence of one or the other factor provoked the same loss of localization accuracy and even much the same error pattern. Head movement analysis showed that subjects turn their face towards the emitting sound source, except for sources exactly in the front or exactly in the rear, which are identified by turning the head to both sides. The head movement amplitude increased smoothly as the sound source moved from the anterior to the posterior quadrant.

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