Byoungho Kwon

Analysis of the GCC-PHAT technique for multiple sources

Techniques to estimate the time delay of arrival (TDOA) using the measurements of the acoustic signals by microphones have been studied in various fields such as the robot auditory system, teleconference system and speech recognition system. One common method of determining TDOA is to compute the cross correlation function. The Generalized Cross Correlation (GCC) method, which calculates the correlation function by using inverse Fourier transformation of the cross power spectral density function multiplied by the proper weighting function, was proposed by Knapp and Cater in 1976. This method analyzed the weighting functions to estimate the optimal TDOA for a single source. In this paper, we derived the cross correlation function by GCC method with PHAT weighting function for multiple sources and ascertained the relationship between the correlation value and source characteristics. Moreover, we compared the derived GCC function for two sources case with the real GCC function calculated by the actual signals and verified their similarity.

Sound Source Localization Methods with Considering of Microphone Placement in Robot Platform

Many different methods for sound source localization have been developed. Most of them mainly depend on time difference of arrival (TDOA) or analytic head related transfer functions (HRTF). In real implementation, since the direct path between a source and a sensor is interrupted by obstacles as like a head or body of robot, it has to be considered the number of sensors as well as their positions. Therefore, in this paper, we present the methods, which are included sensor position problem, to localize the sound source with 4 microphones to cover the 3D space. Those are modified two-step TDOA methods. Our conclusion is that the different method has to be applied in case to be different microphone position on real robot platform.

Sound source localization for robot auditory system using the summed GCC method

A variety of methods for sound source localization applied to robot auditory system have been developed. Most of them mainly depend on the time difference of arrival (TDOA) between microphones because of light computational load and easy application. Generally, possible region to localize the source, whatever localization methods are used, depends on the number of microphones. In case of the localization method based on TDOA, minimum four microphones which donpsilat all lie in the same plane are needed to estimate the source direction in 3D space. However, the new approach based on the summed GCC method can estimate the source direction in 3D space utilizing three microphones only and the platform effect. Because microphones for the robot auditory system are usually installed on the outer robot platform the proposed algorithm is quite suitable for robot applications. Difference between mapping functions caused by robot platform makes the source localization in 3D space with three microphones only be possible. We have shown a case where the sound source localization in some restricted region of the 3D space is possible by using the proposed approach through the ideal simulation.

Sound Source Localization Method Using Spatially Mapped GCC Functions

Sound source localization method based on the time delay of arrival(TDOA) is applied to many research fields such as a robot auditory system, teleconferencing and so on. When multi-microphones are utilized to localize the source in 3 dimensional space, the conventional localization methods based on TDOA decide the actual source position using the TDOAs from all microphone arrays and the detection measure, which represents the errors between the actual source position and the estimated ones. Performance of these methods usually depends on the number of microphones because it determines the resolution of an estimated position. In this paper, we proposed the localization method using spatially mapped GCC functions. The proposed method does not use just TDOA for localization such as previous ones but it uses spatially mapped GCC functions which is the cross correlation function mapped by an appropriate mapping function over the spatial coordinate. A number of the spatially mapped GCC functions are summed to a single function over the global coordinate and then the actual source position is determined based on the summed GCC function. Performance of the proposed method for the noise effect and estimation resolution is verified with the real environmental experiment. The mean value of estimation error of the proposed method is much smaller than the one based on the conventional ones and the percentage of correct estimation is improved by 30% when the error bound is .

Spatially Mapped GCC Function Analysis for Multiple Source and Source Localization Method

A variety of methods for sound source localization have been developed and applied to several applications such as noise detection system, surveillance system, teleconference system, robot auditory system and so on. In the previous work, we proposed the sound source localization using the spatially mapped GCC functions based on TDOA for robot auditory system. Performance of the proposed one for the noise effect and estimation resolution was verified with the real environmental experiment under the single source assumption. However, since multi-talker case is general in human-robot interaction, multiple source localization approaches are necessary. In this paper, the proposed localization method under the single source assumption is modified to be suitable for multiple source localization. When there are two sources which are correlated, the spatially mapped GCC function for localization has three peaks at the real source locations and imaginary source location. However if two sources are uncorrelated, that has only two peaks at the real source positions. Using these characteristics, we modify the proposed localization method for the multiple source cases. Experiments with human speeches in the real environment are carried out to evaluate the performance of the proposed method for multiple source localization. In the experiments, mean value of estimation error is about and percentage of multiple source localization is about 62% on average.

Sound source localization using the compensation method in robot platform

While various methods for sound source localization have been developed, most of them utilize on the time difference of arrival (TDOA) between microphones or the measured head related transfer functions (HRTF). In case of a real robot implementation, the former has a merit of light computation load to estimate the sound direction but can not consider the effect of platform on TDOAs, while the latter can, because characteristics of robot platform are included in HRTF. However, the latter needs large resources for the HRTF database of a specific robot platform. We propose the compensation method which has the light computation load while the effect of platform on TDOA can be taken into account. The proposed method is used with spherical head related transfer function (SHRTF) on the assumption that robot platform, for example a robot head, installed microphones can be modeled to a sphere. We verify that the proposed method decreases the estimation error caused by the robot platform through the simulation.

Active Window to Reduce the Exterior Noise Flowed Through the Open Window

Recently, noise has been regarded as one of the most notorious and frequent environmental pollutions which can be often encountered not only in the living space but also in the industrial site. Studies on physiological and psychological effects of long-term noise exposure to human being have commanded the public interest on noise issues. Since environmental noises such as traffic noise and construction noise is mainly flowed through the open window, it is necessary to develop the active noise control system to reduce it inside the building. Although control speakers and microphones for the noise signal measurement in the control region are essential for the conventional active noise control methods, it is impossible to implement them in the control region in the building environment because the control region is the living quarter and they may hinder activities of the residents. Therefore, we proposed the active window system to reduce the exterior noise flowed through the open window with microphones installed outside the window and control speakers installed at the frame of the window. To confirm the performance of the proposed active window, we carried out the simulation and experiment using active window system with 8 control speakers. Simulation results showed the noticeable noise reduction effect inside the control region within the frequency range without the spatial aliasing. Experimental result showed that the total acoustic potential energy inside the room of the scale model is reduced to about 10dB within the interest of frequency range.

Factors for Speech Signal Time Delay Estimation

Since it needs the light computational load and small database, sound source localization method using time delay of arrival(TDOA method) is applied at many research fields such as a robot auditory system, teleconferencing and so on. Researches for time delay estimation, which is the most important thing of TDOA method, had been studied broadly. However studies about factors for time delay estimation are insufficient, especially in case of real environment application. In 1997, Brandstein and Silverman announced that performance of time delay estimation deteriorates as reverberant time of room increases. Even though reverberant time of room is same, performance of estimation is different as the specific part of signals. In order to know that reason, we studied and analyzed the factors for time delay estimation using speech signal and room impulse response. In result, we can know that performance of time delay estimation is changed by different R/D ratio and signal characteristics in spite of same reverberant time. Also, we define the performance index(PI) to show a similar tendency to R/D ratio, and propose the method to improve the performance of time delay estimation with PI.

Vector Base Amplitude Panning Based Noise Control Method for Improving the Amenity in Building Environment

A variety of noise control methods have been developed as an interest on noise issues increases. Among them, noise control methods using masking effect, a phenomenon to reduce the ability to notice the unwanted sound by proper sound, to implement a pleasant sound environment have been studied under the name of soundscape. We proposed a novel vector base amplitude panning(VBAP) based noise control method to apply to the building environment. The proposed method could improve the amenity inside the building to reproduce the sounds with excellent masking effect on the incoming path of noise using the control speakers, considering the direction of noise source. The directional masking sounds can be generated by using VBPA technique. To verify the performance of the proposed method, we carried out the subjective test for the degree of amenity according to direction of the masking sound. Subjective test results showed that it is possible to improve the amenity inside the building by controlling the direction of masking sound considering the human`s auditory characteristic.