| With the developments of multimedia technology,the importance of using voice in receiving and dealing with information has aroused wild concern. The applications of voice recognition,voice enhancement and acoustic source localization are still under development,while acoustic source localization is the basis and prerequisite. Acoustic source localization based on microphone array has received more and more attention because it has potential for a broad range of applications.In our thesis,we dedicate ourselves to research and realization of acoustic source localization system based on microphone array in room environment. The performance of microphone array is affected seriously due to room reverberation and environment noise. Another question,restrained by harware conditions,some localization algorithm is computational burdensome,thus can not be applied in real time applications. To deal with these two crucial questions,we put forward our own solutions,and we designed a real acoustic source localization system,using which,we collect voice data,validate our proposed algorithm and solution.In light of the importance of preprocess and voice activity detection to the following treatments in acoustic localization system,first,we give an introduction of filtering,windows,explained two simple but effective voice activity detection algorithms: energy discriminator and zero-crossing.Two steps method,namely,GCC-LMS based on TDOA is widely used in realistic system due to its low computational cost.Time delay estimation in the first step will determine the performance of localization.We find out that false peak at zero point will lead to false time delay estimation due to synchronous noise,in order to solve this problem,we filter the cross spectrum.To restrain effects of reverberation and noise,we take the following measures, 1 )reduce the search region according to the distances of microphones,2)adjust the weight factor dynamically according to signal noise ratio. Simulation results show that the accuracy of time delay estimation is improved in environment with high noise and reverberation .In addition,we propose a method to interpolate the cross correlation function in low sampling rate,which raise the space resolution.In the second step of TDOA,LMS is widely used.In order to make our system more reliable and more robust ,we use every microphone as reference microphone in turn, then we get a couple of source locations.Getting rid of some source locations with large error, averaging the remaining source locations,we get a more reasonable and trusty source location. Besides, we give a brief introduction of two-dimensional geometry localization method,and compare it with LMS.Another popular method is SRP(Steered Beamforming),which is a one-step localization method,and it delays the phase of making a decision,integrates all the microphone information.,thus makes itself more resistant to noise and reverberation. The corresponding shortcoming is its larger computational cost,hardly suitable for real time processing. Steered beamforming method based on stochastic region contraction (SRP-SRC) avoids global searching,greatly reduces computational cost.In our thesis, we put forward a new method,namely SRP-RSRC to improve SRP-SRC,in which,1)a shaping function is brought in,thus increase the contrast of energy peak,2)set a energy threshold,search the biggest energy point in the volumes where their energy are greater than the threshold,make SRP-SRC convergence more quickly,and is more computational efficient. Besides. A combination of kalman estimation and filter with SRP-RSRC is also raised,which makes tracking more robust and stalbe.In the end,we describle our real acoustic localization system in room environment,including its architecture,software,and hardware. Voice data is acquired from this system ,with which,a comparison is made between GCC-LMS and SRP-SRC,SRP-RSRC. |
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