A Real-Time Multiple Acoustic Sources Localization Method Using Widely Spaced Microphone Array

2013 ◽  
Vol 391 ◽  
pp. 580-583 ◽  
Author(s):  
Tian Yi Gu ◽  
Zhao Zhao ◽  
Ya Qi Wu ◽  
Zhi Yong Xu ◽  
Jing Yi Wang
Keyword(s):  
Real Time ◽  
Microphone Array ◽  
Localization Method ◽  
Cluster Process ◽  
Sound Detection ◽  
Acoustic Sources ◽  
Phase Differences

A real-time disambiguous localization method for multiple acoustic sources using widely spaced microphone array is proposed in this paper. The observation signals in each frame are firstly discriminated utilizing conventional energy-based sound detection measurement. Using inter-microphone phase differences (IPD), as well as an iterative cluster process, the DOAs of sources can be estimated while the phase wrapping ambiguity in conventional DUET is avoided.

Assessment of MUSIC-Based Noise-Robust Sound Source Localization with Active Frequency Range Filtering

2018 ◽  
Vol 30 (3) ◽  
pp. 426-435 ◽  
Author(s):  
Kotaro Hoshiba ◽  
Kazuhiro Nakadai ◽  
Makoto Kumon ◽  
Hiroshi G. Okuno ◽  
◽  
...  
Keyword(s):  
Real Time ◽  
Source Localization ◽  
Sound Source ◽  
Microphone Array ◽  
Sound Source Localization ◽  
Noise Robustness ◽  
Frequency Range ◽  
Real Time Processing ◽  
Time Processing ◽  
Localization Method

We have studied sound source localization, using a microphone array embedded on a UAV (unmanned aerial vehicle), for the purpose of detecting for people to rescue from disaster-stricken areas or other dangerous situations, and we have proposed sound source localization methods for use in outdoor environments. In these methods, noise robustness and real-time processing have a trade-off relationship, which is a problem to be solved for the practical application of the methods. Sound source localization in a disaster area requires both noise robustness and real-time processing. For this we propose a sound source localization method using an active frequency range filter based on the MUSIC (MUltiple Signal Classification) method. Our proposed method can successively create and apply a frequency range filter by simply using the four arithmetic operations, so it can ensure both noise robustness and real-time processing. As numerical simulations carried out to compare the successful localization rate and the processing delay with conventional methods have affirmed the usefulness of the proposed method, we have successfully produced a sound source localization method that has both noise robustness and real-time processing.

scholarly journals Speaker Localization Based on Audio-Visual Bimodal Fusion

2021 ◽  
Vol 25 (3) ◽  
pp. 375-382
Author(s):  
Ying-Xin Zhu ◽  
Hao-Ran Jin ◽  
◽  
◽  
Keyword(s):  
Microphone Array ◽  
Single Mode ◽  
Frame Rate ◽  
Multimodal Fusion ◽  
Mode Localization ◽  
Localization Method ◽  
Adaboost Algorithm ◽  
Speaker Localization ◽  
The Stability ◽  
Stability And Accuracy

The demand for fluency in human–computer interaction is on an increase globally; thus, the active localization of the speaker by the machine has become a problem worth exploring. Considering that the stability and accuracy of the single-mode localization method are low, while the multi-mode localization method can utilize the redundancy of information to improve accuracy and anti-interference, a speaker localization method based on voice and image multimodal fusion is proposed. First, the voice localization method based on time differences of arrival (TDOA) in a microphone array and the face detection method based on the AdaBoost algorithm are presented herein. Second, a multimodal fusion method based on spatiotemporal fusion of speech and image is proposed, and it uses a coordinate system converter and frame rate tracker. The proposed method was tested by positioning the speaker stand at 15 different points, and each point was tested 50 times. The experimental results demonstrate that there is a high accuracy when the speaker stands in front of the positioning system within a certain range.

Multimodal Human Localization Using Bayesian Network Sensor Fusion

2007 ◽  
pp. 194-221 ◽  
Author(s):  
David Lo
Keyword(s):  
Bayesian Network ◽  
Microphone Array ◽  
Human Subjects ◽  
Video Conferencing ◽  
Localization Method ◽  
Talker Localization ◽  
Security Surveillance ◽  
Audio Video ◽  
Surveillance Applications

In applications where the locations of human subjects are needed, for example, human-computer interface, video conferencing, and security surveillance applications, localizations are often performed using single sensing modalities. These mono localization modalities, such as beamforming microphone array and video-graphical localization techniques, are often prone to errors. In this chapter, a modular multimodal localization framework was constructed by combining multiple mono localization modalities using a Bayesian network. As a case study, a joint audio-video talker localization system for the video conferencing application was presented. Based on the results, the proposed multimodal localization method outperforms localization methods, in terms of accuracy and robustness, when compare with mono modal modalities that rely only on audio or video.

Real-time UAV sound detection and analysis system

2017 ◽  
Author(s):  
Juhyun Kim ◽  
Cheonbok Park ◽  
Jinwoo Ahn ◽  
Youlim Ko ◽  
Junghyun Park ◽  
...  
Keyword(s):  
Real Time ◽  
Sound Detection ◽  
Analysis System
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