• Journal of KIISE
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• v.43 no.1
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• pp.13-26
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• 2016

This paper proposes a new sound localization algorithm that can improve localization performance based on a tetrahedron-shaped microphone array. Sound localization system estimates directional information of sound source based on the time delay of arrival(TDOA) information between the microphone pairs in a microphone array. In order to obtain directional information of the sound source in three dimensions, the system requires at least three microphones. If one of the microphones fails to detect proper signal level, the system cannot produce a reliable estimate. This paper proposes a tetrahedron- shaped sound localization system with a coordinate transform method by adding one microphone to the previously known triangular-shaped system providing more robust and reliable sound localization. To verify the performance of the proposed algorithm, a real time simulation was conducted, and the results were compared to the previously known triangular-shaped system. From the simulation results, the proposed tetrahedron-shaped sound localization system is superior to the triangular-shaped system by more than 46% for maximum sound source detection.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.72-77
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• 2024

Recently, the necessity for sound source localization has grown significantly across various industrial sectors. Among the sound source localization methods, sound intensimetry has the advantage of having high accuracy even with a small microphone array. However, the increase in localization error at high Helmholtz numbers have been pointed out as a limitation of this method. The study proposes a method to compensate for the bias error of the measured sound intensity vector according to the Helmholtz numbers by applying deep learning. The method makes it possible to estimate the accurate direction of arrival of the source by applying a dense layer-based deep learning model that derives compensated sound intensity vectors when inputting the sound intensity vectors measured by a tetrahedral microphone array for the Helmholtz numbers. The model is verified based on simulation data for all sound source directions with 0.1 < kd < 3.0. One can find that the deep learning-based approach expands the measurement frequency range when implementing the sound intensimetry-based sound source localization method, also one can make it applicable to various microphone array sizes.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.573-578
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• 2003

Recently, speaker localizing estimation technique has been rising in teleconference systems. In this paper, it was described to be able to enhance the speech quality through microphone array, and received the only signal of speaker. Unfortunately, as it using estimated the signal in advance, it is not matched in a real acoustic environment so it has poor performance. In this paper is proposed for Adaptive Matched Filter Microphone Array that estimated acoustic room environment from the received the signal and study of the efficiency through simulations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.34-44
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• 2010

In this study, the algorithms for multichannel format conversion and robust representation of spatial sound information are proposed. In the spatial analysis, the directional information of sound source is estimated and sound sources are separated from stereo signal. In the spatial resynthesis, the multichannel matrixing with spatial repanning and post-scaling method are applied to represent a spatial sound. The conventional method about channel format conversion has the problem that the energy of sound source and the spatial information are not preserved in the desired channel format. Because the proposed method is designed in consideration of the target multichannel format and its resynthesized signal, the robust representation of spatial sound can be achieved in the multichannel format conversion.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.71-78
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• 2009

Sound source localization systems in service robot applications estimate the direction of a human voice. Time delay information obtained from a few separate microphones is widely used for the estimation of the sound direction. Correlation is computed in order to calculate the time delay between two signals. In addition, PHAT weighting function can be applied to significantly improve the accuracy of the estimation. However, FFT and IFFT operations in the PHAT weighting function occupy more than half of the area of the sound source localization system. Thus efficient FFT and IFFT designs are essential for the IP implementation of sound source localization system. In this paper, we propose an efficient FFT/IFFT design method based on the characteristics of human voice.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.737-743
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• 2011

Service robots are equipped with various sensors such as vision camera, sonar sensor, laser scanner, and microphones. Although these sensors have their own functions, some of them can be made to work together and perform more complicated functions. AudioFvisual fusion is a typical and powerful combination of audio and video sensors, because audio information is complementary to visual information and vice versa. Human beings also mainly depend on visual and auditory information in their daily life. In this paper, we conduct two studies using audioFvision fusion: one is on enhancing the performance of sound localization, and the other is on improving robot attention through sound localization and face detection.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.115-122
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• 2011

In this paper, we present a method to estimate an accurate real-time sound source direction based on time delay of arrival by using generalized cross correlation with four cross-type microphones. In general, existing systems have two disadvantages such as system embedding limitation due to the necessity of data acquisition for signal processing from microphone input, and real-time processing difficulty because of the increased number of channels for sound direction estimation using DSP processors. To cope with these disadvantages, the system considered in this paper proposes hardware design for enhanced real-time processing using microphone array signal processing. An accurate direction estimation and its design time reduction is achieved by means of an efficient hardware design using spatial segmentation methods and verification techniques. Finally we develop a system which can be used for embedded systems using a sound codec and an FPGA chip. According to experimental results, the system gives much faster real-time processing time compared with either PC-based systems or the case with DSP processors.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.178-183
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• 2024

This study introduces an enhanced sound source localization technique, bolstered by a data-driven deep learning approach, to improve the precision and accuracy of direction of arrival estimation. Focused on refining Time Difference Of Arrival (TDOA) based sound source localization, the research hinges on accurately estimating TDOA from cross-correlation functions. Accurately estimating the TDOA still remains a limitation in this research field because the measured value from actual microphones are mixed with a lot of noise. Additionally, the digitization process of acoustic signals introduces quantization errors, associated with the sampling frequency of the measurement system, that limit the precision of TDOA estimation. A deep learning-based approach is designed to overcome these limitations in TDOA accuracy and precision. To validate the method, we conduct comprehensive evaluations using both two and three-microphone array configurations. Moreover, the feasibility and real-world applicability of the suggested method are further substantiated through experiments conducted in an anechoic chamber.

• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.419-424
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• 2017

TDoA (Time Difference-of Arrival) or DoA (Direction-of-Arrival) can be used for source localization. However, the localizing performance is dependent on relative position between source and receivers, receivers' geometric structure, sound speed, and so on. In this paper we propose a source localization method with enhanced performance that combines multiple information. The proposed method uses the time TDoA, DoA and sound speed as variables. LM (Levenberg-Marquardt) method which is one of nonlinear optimizations is applied. The performances of the proposed method was evaluated by simulation. As result of simulation, the proposed method has the lower average localizing error performance than the previous method.

• The Journal of Engineering Research
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• v.8 no.1
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• pp.59-65
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• 2006

본 논문에서는 마이크로폰 어레이 시스템을 이용하여 여러 화자의 음성 정보로부터 각 화자가 위치한 방향을 추정하는 기술 개발 내용을 다룬다. 성능 향상을 위한 전처리 과정으로 비선형 증폭기를 사용하여 거리에 따른 영향을 최소화하는 과정과 잡음에 대한 강인성을 얻기 위해 음성활성 영역을 검출하는 과정을 포함한다. 등간격으로 배치된 마이크로폰 어레이 시스템의 기하학적 특성에 따른 음원의 위치와 신호의 지연시간차이와의 상관관계로부터 화자의 위치를 역으로 추정하는 알고리즘을 기본으로 하여 가능성 척도를 계산하고 이를 활용하여 가능성이 높은 것들을 클러스터링하여 가능성이 있는 후보를 선정하여 화자의 방향을 검지한다. 이 과정에서 오인식을 최소화하기 위하여 가능성이 희박한 영역에 대한 추정 억제 방법으로 부정식 추론법을 적용하였다. 2 화자의 음성 신호를 입력으로 한 실험을 통하여 제안한 방법에 의한 다화자 방향검지의 가능성을 알아보았다.