• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.90-97
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• 2004

In this paper, the optimal position selection of error microphones and control speakers to attenuate interior noise from outside noise sources using active noise control techniques is presented. To get an optimal control characteristics of adaptive noise control systems, it is necessary to optimize the positions of microphones and speakers. New type of simulated annealing method has been proposed as searching techniques to find optimal speakers and microphones positions in which the sum of the squared pressures at microphone positions in an enclosure can be best minimized. Computer simulations and experiments have been performed to show the effectiveness of the proposed method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1268-1278
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• 2004

Measurement of noise is not only to know the information of acoustic pressure but to assess human response to noise. To find human response to transportation noise through the laboratory study we have to measure and reproduce noise. The method of noise reproduction is largely divided into monaural and binaural techniques. But human fundamentally hears sound through both ears, referred as binaural hearing. Binaural signal is different from monaural signal because it includes more information of physical phenomena like acoustical reflection, diffraction and refraction. Especially head and pinna play an important role in perceiving change of signal origin. So, the amplitude of binaural signal is higher than that of monaural signal and spectrum of both signals is discriminated. Most of assessment and regulation of transportation noise are, however, based on monaural measurement techniques. The quantitative difference between monaural and binaural measurement is investigated in this study. Comparison on several transportation noisesshows defect of information in monaural measurements.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.911-915
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• 2004

Recently, several experimental techniques for identifying the noise sources distributed over a moving vehicle are being developed and used in order to design a low noise vehicle. The beamforming method, which uses phase information between several microphones to localize the source position, is proved to be one of the promising techniques applicable even under complicated test environments. In this study a beamforming algorithm is developed and applied to measure the dominant noise sources on a passenger car moving at constant speed. Unlike the acoustic signals from a stationary noise source, the sound generated from a moving source is distorted due to the Doppler effects. The sound pressure are measured with an spiral array system composed of 26 microphones and a pair of photo sensors are used to measure the. vehicle speed. The information about the speed and relative position of the vehicle are used to eliminate the Doppler effects from the measured pressure signal by using a de-Dopplerization algorithm. The noise generated from a moving vehicle can be grouped in many ways, however, tire noise and the noise generated from the engine are distinguishable at the speeds being tested.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.4
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• pp.185-194
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• 2013

Abstract- In distant-talking environments, speech recognition performance degrades significantly due to noise and reverberation. Recent work of Michael L. Selzer shows that in microphone array speech recognition, the word error rate can be significantly reduced by adapting the beamformer weights to generate a sequence of features which maximizes the likelihood of the correct hypothesis. In this approach, called Likelihood Maximizing Beamforming algorithm (Limabeam), one of the method to implement this Limabeam is an UnSupervised Limabeam(USL) that can improve recognition performance in any situation of environment. From our investigation for this USL, we could see that because the performance of optimization depends strongly on the transcription output of the first recognition step, the output become unstable and this may lead lower performance. In order to improve recognition performance of USL, some post-filter techniques can be employed to obtain more correct transcription output of the first step. In this work, as a post-filtering technique for first recognition step of USL, we propose to add a Wiener-Filter combined with Feature Weighted Malahanobis Distance to improve recognition performance. We also suggest an alternative way to implement Limabeam algorithm for Hidden Markov Network (HM-Net) speech recognizer for efficient implementation. Speech recognition experiments performed in real distant-talking environment confirm the efficacy of Limabeam algorithm in HM-Net speech recognition system and also confirm the improved performance by the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.61-68
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• 2015

Noise reduction is necessary to compensate for the degradation of recognition performance by various types of noises. Among many noise reduction techniques using microphone array, generalized sidelobe canceller (GSC) has been widely applied to reduce nonstationary noises. The performance of GSC is directly affected by its adaptation mode controller (AMC). That is, accurate target speech detection is essential to guarantee the sufficient noise reduction in pure noise intervals and the less distortion in target speech intervals. Thus, this paper proposes an improved AMC design technique in which the power ratio of the output of fixed beamforming to that of blocking matrix is calculated frequency bandwise and probabilistically modeled by mixture Gaussians for each class. Experimental results show that the proposed algorithm outperforms conventional AMCs in receiver operating curves (ROC) and output SNRs.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2265-2271
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• 1994

With the improvement of standard of living, requirement for comfortable and quiet environment has been increased and, therefore, there has been a many researches for active noise reduction to overcome the limit of passive control method. In this study, active noise control is performed in a duct system using intelligent control technique which needs not decide the coefficients of high order filter and the mathematical modeling of a system. Back propagation algorithm is applied as an intelligent control technique and control system is organized to exclude the error microphone and high speed operational device which are indispensable for conventional active noise control techniques. Furthermore, learning is performed by organizing acoustic feedback model, and the effect of the proposed control technique is verified via computer simulation and experiment of active noise control in a duct system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.109-114
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• 2004

Measurement of noise is not only to know the information of acoustic pressure but to assess human response for noise. Provided that want to find human response for transportation noise, we will have to reproduce the measured noise. The method of reproduction is largely divided into monaural and binaural reproduction techniques. Human fundamentally hears sound through both ears, which is binaural hearing. And binaural technique includes the more information of physical phenomena like acoustical reflection and deflection. So, binaural reproduction is more suitable for assessment of the psychoacoustical and physiological response for transportation noise exposures.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.2
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• pp.157-163
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• 2004

Optimal transducer positions are important as much as the control algorithms and hardware performance in the active noise control system. This study is similar to the past researches on the optimal transducer locations but with a far field noise source having a plane wave characteristic and the noise coming through an opening such as a window in an enclosure. Optimization techniques are used to find sets of optimal loudspeaker positions from a larger possible loudspeaker positions. Loudspeakers are placed on the surface of opening at the wall and inside of the enclosure. Using the measured acoustic transfer impedances and numerical simulations with the optimization technique, optimal positions are identified and compared. When a small number of loudspeakers are used. loudspeaker positions on the opening near the center seems to be the best place, but when a larger number of loudspeakers are used it was difficult to find simple patterns in the optimal positions. With the optimally positioned loudspeakers, optimal microphone positions are also studied.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.837-842
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• 2004

The positions of rotating sound sources have been localized by experiments with the Doppler effects removed. In order to do-Dopplerize the sound signals emitted from moving sources, two kinds of signal reconstruction methods were applied. One is the forward propagation method and the other is the backward propagation method. Forward propagation method analyze the source emission time based on the instantaneous distance between sensors and the assumed source position, then the signals are reconstructed with respect to the emission time. On the other hand, the backward method uses time delay to do-Dopplerize the acquired data for the received time of reference. In both techniques, the reconstructed signal data were processed using beamforming algorithm to produce power distributions at the frequency of interest. Experiments have been carried out for varying frequencies, rotating speeds and the object distances. Forward propagation method has shown better performance in locating source position than the backward propagation method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.630-633
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• 2021

Microphones can convert received voice signals to electric signals. They have been widely used in various industries such as radios, smart devices and vehicles. Recently, the demands for small size and high sensitive microphones are increased according to the minimization of wireless earphone with the development of smart phone. A MEMS system is a good candidate for an ultra-small size microphone of a next generation and a read out IC for high sensitive MEMS sensor is researched from many industries and academies. Since the microphone system has a high sensitivity from environment noise and electric system noise, the system requires a low noise power supply and some low noise design techniques. In this paper, a low noise LDO is presented for small size MEMS microphone systems. The input supply voltage of the LDO is 1.5-3.6V, and the output voltage is 1.3V. Then, it can support to 5mA in the light load condition. The integrated output noise of proposed LDO form 20Hz to 20kHz is about 1.9uV. These post layout simulation results are performed with TSMC 0.18um CMOS technology and the size of layout is 325㎛ × 165㎛.