• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.1003-1008
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• 2001

In beamforming method, source positions are predicted by MUSIC (Multiple Signal Classification) power method and composite sound fields can then be decomposed into each partial field by beamforming, detenninistically without restriction of the distance between reference microphones and sources. However, reference microphone array shape is important in both MUSIC and beamforming method. Thus the present paper describes the effect of the reference microphone array shape.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.164-169
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• 2005

Microphone array techniques are being used widely in wind tunnel measurements for identification of the distributed aerodynamic noise sources on the model being tested. Depending on the frequencies and sound levels, conventional beamforming algorithm has limitation in separating two adjacent sources. Several modifications to the classical beamforming have been developed to enhance way resolution and reduce sidelobe levels. In this Paper the robust adaptive beamforming and the CLEAN algorithm are used to compare to the result of conventional beamforming method. It is found that the CLEAN algorithm is capable of pin-pointing locations of multiple sources nearby, while these sources are unidentifiable with robust adaptive or conventional beamforming techniques.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.92-96
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• 2007

Microphone array beamforming method has been recognized as an important aeroacoustic research field and become a standard technique in localizing sound sources. This method also used in flight acoustic measurement, and especially, it is very useful when measure sounds inside the wind tunnel. In measuring sound which is inside the wind tunnel by traditional beamforming method, there are some errors caused by airstream. The speed and the propagation path of the sound changes as it travel through the airstream. This makes the error which the position of sound is changed a little bit to the down stream direction. In this paper, validation test has made about the correction equation for this wind effects of previous researches. And beamforming including shear layer correction was performed about a sound source in the anechoic open-jet windtunnel.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.6
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• pp.612-618
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• 2008

Microphone array beamforming method has been recognized as an important aeroacoustic research field and become a standard technique in localizing sound sources. This method also used in flight acoustic measurement, and especially, it is very useful when measure sounds inside the wind tunnel. In measuring sound which is inside the wind tunnel by traditional beamforming method, there are some errors caused by airstream. The speed and the propagation path of the sound changes as it travel through the airstream. This makes the error which the position of sound is changed a little bit to the down stream direction. In this paper, validation test has made about the correction equation for this wind effects of previous researches. And beamforming including shear layer correction was performed about a sound source in the anechoic open-jet wind tunnel.

• Phonetics and Speech Sciences
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• v.4 no.4
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• pp.87-92
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• 2012

Speech enhancement aims to improve speech quality by removing background noise from noisy speech. Independent vector analysis is a type of frequency-domain independent component analysis method that is known to be free from the frequency bin permutation problem in the process of blind source separation from multi-channel inputs. This paper proposed a new method of microphone array based speech enhancement that combines independent vector analysis and beamforming techniques. Independent vector analysis is used to separate speech and noise components from multi-channel noisy speech, and delay-sum beamforming is used to determine the enhanced speech among the separated signals. To verify the effectiveness of the proposed method, experiments for computer simulated multi-channel noisy speech with various signal-to-noise ratios were carried out, and both PESQ and output signal-to-noise ratio were obtained as objective speech quality measures. Experimental results have shown that the proposed method is superior to the conventional microphone array based noise removal approach like GSC beamforming in the speech enhancement.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.838-839
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• 2013

In this paper, optimum beamforming method using spherical microphone array is presented. Beamforming method has been recognized as an important study in localizing sound sources or visualizing acoustic fields in three-dimensional space. Its geometrical arrangement of sensors in space enables to process array signal to analyze the fields of interest by steering array response in three-dimensional.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.611-614
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• 2021

In this paper, we propose a widerange array microphone for lecturer tracked with Frequency Modulated Continuous Waveform (FMCW) radar sensor. Time Difference-of-Arrival (TDoA) is often used as audio tracking, but the tracking accuracy is poor because the frequency of the voice is low and the relative frequency change is large. FMCW radar has a simple structure and is used to detect obstacles for vehicles, and the resolution can be archived to several centimeter. It is shown that the sensor is useful for detecting a speaker in open area such as a lecture, and we propose an wide range 4-element array microphone beamforming system. Through some experiments, the proposed system is able to adequately track the location and showed a 8.6dB improvement over the selection of the best microphone.

• MALSORI
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• no.66
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• pp.73-86
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• 2008

Beamforming is one of the spatial filtering techniques which extract only desired signals from noisy environments using microphone arrays. Fixed beamforming is a simple concept and easy to implement. However, it does not show good performance in real noisy conditions. As an adaptive beamforming, Frost algorithm can be a good candidate. It uses the concept of the linearly constrained minimum variance (LCMV) algorithm. The difference between the Frost and the LCMV algorithm is the error correction scheme which is very effective feature in the aspect of performance. In this paper, as quadrature mirror filtering (QMF)-based filterbank is utilized as the pre-processing of the Frost beamformning, the filter length and the learning rate of each band is optimized to improve the performance. The performance is measured by the signal-to-noise ratio (SNR) and the Bark's scale spectral distortion (BSD).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.334-337
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• 2005

The speech intelligibility is one of the most important factors in communication system. The speech intelligibility is related with speech to noise ratio. To enhance the speech to noise ratio, background noise reduction techniques are being developed. As a part of solution to noise reduction, this paper introduces directional microphone using beamforming method and speech filtering method. The directional microphone narrows the spatial range of processing signal into the direction of the target speech signal. The noise signal located in the same direction with speech still remains in the processing signal. To sort this mixed signal into speech and noise, as a following step, a speech-filtering method is applied to pick up only the speech signal from the processed signal. The speech filtering method is based on the characteristics of speech signal itself. The combined directional microphone and speech filtering method gives enhanced performance to speech intelligibility in communication system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.7 s.112
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• pp.677-682
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• 2006

In the case of aeroacoustic test in windtunnel, measurement accuracy is reduced by not only Doppler effects but also by the microphone self noise due to airflow and high turbulence in the wall boundary layer. Microphone array measurements can be easily utilized for the solutions of these problems. In this paper, geometrical optics approach and diagonal term elimination of cross spectral matrix was introduced to the de-dopplerization and self noise reduction methods for the microphone array measurement. For the validation, beamforming tests for sinusoidal point source were performed in the closed type test section of windtunnel, and their performances of beam width and sidelobe rejection were significantly improved.