Real-time Sound Localization Research Articles

Real-time Sound Localization Using Generalized Cross Correlation Based on 0.13 ㎛ CMOS Process

In this paper, we present the design and implementation of real-time sound localization based on 0.13 m CMOS process. Time delay of arrival (TDOA) estimation was used to obtain the direction of the sound signal. The sound localization chip consists of four modules: data buffering, short-term energy calculation, cross correlation, and azimuth calculation. Our chip achieved real-time processing speed with full range (360°) using three microphones. Additionally, we developed a dedicated sound localization circuit (DSLC) system for measuring the accuracy of the sound localization chip. The DSLC system revealed that our chip gave reasonably accurate results in an experiment that was carried out in a noisy and reverberant environment. In addition, the performance of our chip was compared with those of other chip designs.

반향음과 잡음 환경을 고려한 실시간 소리 추적 시스템

소리를 이용한 위치 추적은 마이크로폰을 이용하여 신호를 수집하고 수집된 신호로 부터 마이크로폰 간의 신호 도달 시간차를 추정한 뒤 추정된 시간차를 이용하여 소리의 발생 위치를 추정하는 과정을 거치게 된다. 실내 환경에서 이를 활용하기 위해서는 잡음과 반향음에 대한 강건성을 확보해야만 하는 제약이 따른다. 특히 실시간으로 구현하기 위해서는 계산의 효율성까지 고려되어야 한다. 본 논문에서는 네 개의 저가 콘덴서 마이크로폰을 이용하여 비용적인 측면과 계산량에서의 효율성을 모두 추구하였다. 네 개의 마이크로폰을 이용하여 마이크로폰 간의 소리 도달 시간차를 구하는 계산량을 줄였고 GCC-PHAT(Generalized Cross Correlation-Phase Transform) 알고리즘을 이용해서 강건성을 높였으며 iterative least square 방식을 이용하여 높은 정확도의 위치 데이터를 얻을 수 있었다. Sound localization algorithm usually adapts three step process: sampling sound signals, estimating time difference of arrival between microphones, estimate location of sound source. To apply this process in indoor environment, sound localization algorithm must be strong enough against reverberant and noisy condition. Additionally, calculation efficiency must be considered in implementing real-time sound localization system. To implement real-time robust sound localization system we adapt four low cost condenser microphones which reduce the cost and total calculation load. And to get TDOA(Time Differences of Arrival) of microphones we adapt GCC-PHAT(Generalized Cross Correlation-Phase Transform) which is robust algorithm to the reverberant and noise environment. The position of sound source was calculated by using iterative least square algorithm which produce highly accurate position data.