• ETRI Journal
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• v.38 no.2
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• pp.235-243
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• 2016

A low-noise readout integrated circuit (ROIC) for a microelectromechanical systems (MEMS) microphone is presented in this paper. A positive feedback signal amplification technique is applied at the front-end of the ROIC to minimize the effect of the output buffer noise. A feedback scheme in the source follower prevents degradation of the noise performance caused by both the noise of the input reference current and the noise of the power supply. A voltage booster adopts noise filters to cut out the noise of the sensor bias voltage. The prototype ROIC achieves an input referred noise (A-weighted) of -114.2 dBV over an audio bandwidth of 20 Hz to 20 kHz with a $136{\mu}A$ current consumption. The chip is occupied with an active area of $0.35mm^2$ and a chip area of $0.54mm^2$.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.269-274
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• 2018

High-sensitivity signal-to-noise ratio (SNR) microphones are essentially required for a broad range of automatic speech recognition applications. Piezoelectric microphones have several advantages compared to conventional capacitor microphones including high stiffness and high SNR. In this study, we designed a new piezoelectric membrane structure by using the finite elements method (FEM) and an optimization technique to improve the sensitivity of the transducer, which has a high-quality AlN piezoelectric thin film. The simulation demonstrated that the sensitivity critically depends on the inner radius of the top electrode, the outer radius of the membrane, and the thickness of the piezoelectric film in the microphone. The optimized piezoelectric transducer structure showed a much higher sensitivity than that of the conventional piezoelectric transducer structure. This study provides a visible path to realize micro-scale high-sensitivity piezoelectric microphones that have a simple manufacturing process, wide range of frequency and low DC bias voltage.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.625-626
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• 2013

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1397-1406
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• 2019

In everyday mobile phone calls between the disabled and non-disabled people due to neurological impairment, the communication accuracy is often hindered by combining the accuracy of pronunciation due to the neurological impairment and the pronunciation features of the disabled. In order to improve this problem, the limiting method is MEMS (micro electro mechanical systems), which includes an induction line that artificially corrects difficult vocalization according to the oral characteristics of the language impaired by improving the word of out of vocabulary. mechanical System) Microphone device improvement. S/W improvement is decision tree with invert function, and improved matrix-vector rnn method is proposed considering continuous word characteristics. Considering the characteristics of H/W and S/W, a similar dictionary was created, contributing to the improvement of speech intelligibility for smooth communication.

• 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㎛.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.949-958
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• 2018

A voice recognition control system is a system for controlling a peripheral device by recognizing a voice. Recently, a voice recognition control system have been applied not only to smart devices but also to various environments ranging from IoT(: Internet of Things), robots, and vehicles. In such a voice recognition control system, the recognition rate is lowered due to the ambient noise in addition to the voice of the user. In this paper, we propose a dual channel acoustic beamforming hardware architecture for MEMS(: Microelectromechanical Systems) microphones to eliminate ambient noise in addition to user's voice. And the proposed hardware architecture is designed as ASIC(: Application-Specific Integrated Circuit) using TowerJazz $0.18{\mu}m$ CMOS(: Complementary Metal-Oxide Semiconductor) technology. The designed dual channel acoustic beamforming ASIC has a die size of $48mm^2$, and the directivity index of the user's voice were measured to be 4.233㏈.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.708-717
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• 2017

Tracking of sound-location is widely used in various area such as intelligent CCTV, video conference and voice commander. In this paper we introduce the real-time sound-location tracking method for smart lecture system using TDoA(Time Difference of Arrival) with orthogonal microphone array on the ceiling. Through discussion on some models of TDoA detection, cross correlation method using linear microphone array is proposed. Orthogonal array with 5 microphone could detect omni direction of sound-location. For real-time detection we adopt the threshold of received energy for eliminating no-voice interval, signed cross correlation for reducing computational complexity. The detected azimuth angles are processed using median filter for lowering the angle deviation. The proposed system is implemented with high performance MCU of TMS320F379D and MEMs microphone module and shows the accuracy of 0.5 and 6.5 in degree for white noise and lectured voice, respectively.

• Journal of Sensor Science and Technology
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• v.30 no.5
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• pp.273-278
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• 2021

Here, we studied the change in the mechanical stiffness of a diaphragm according to the corrugation pattern. The diaphragm consists of a silicon oxide and nitride double layer; a corrugation pattern was formed by dry etching, and the diaphragm was released by wet etching. The fabrication of the thin film was verified using focused ion beam and scanning electron microscopy images. The mechanical stiffness of the diaphragm was obtained by measuring the surface vibration using a laser Doppler vibrometer while applying external sound pressure. Flat squares, diaphragms with square corrugations, and circular corrugation patterns were measured and compared. The stiffness of the diaphragm with a corrugation structure was found to be smaller than that without a corrugation structure; in particular, circular corrugation showed a better effect because of the high symmetry. Furthermore, the effect of corrugation was theoretically predicted. The proposed corrugated diaphragm showed comparable flexibility with the state-of-the-art MEMS microphone diaphragm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.555-567
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• 2019

Speech recognition rate is lowered even in a noisy environment, and it is difficult for a person with a speech disability or an inconvenient language to use it in a social life. In addition to improving the inconvenience of using the language, 280 words were selected using the word selection method which was improved when the word was selected considering the pronunciation characteristics of the language impaired. The MEMS development device used in the experiment was made considering material, lead wire type, length and direction. We improved the speech recognition rate by using the developed word selection method and the MEMS device developed to improve the speech recognition rate due to incorrect pronunciation and severe noise. The new method of selecting words and the mems device were improved and the results were included.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1330-1336
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• 2015

It is necessary to study on acoustic and vibratory response of a MEMS resonant accelerometer before applying to military applications. In this paper, we analyze why the resonant accelerometer reacts to an acoustic wave and a high frequency vibration. And we describe experimental results on acoustic and vibratory response of the accelerometer. The accelerometer consists of a proof mass and a dual ended tuning fork. It is a differential resonant accelerometer with arranging a pair of accelerometers. The mode shape was analyzed to find out the input mode frequency by using a FEM simulation. Some experiments regarding the acoustic noise was carried out by using a tweeter and a microphone in the anechoic room. Results showed that the accelerometer reacted to the acoustic wave and vibration which had the input mode frequency as we had expected. We showed experimentally not only that the susceptibility of the accelerometer to an acoustic wave was 70 dB but also that the effectiveness of applying an acoustic absorber and a metal case was 20 dB, respectively. Also, we could minimize the vibratory response property of the accelerometer by installing a IMU with a silicone rubber mount pad.