• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.259-266
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• 2007

The parameters of electric acoustic characteristic used as standards to evaluate the performance of a small microphone are composed of sensitivity, harmonic distortion, frequency response, directivity and others. Such characteristic parameters should be designed differently depending on a purpose, so it is important to verify whether a small microphone was made appropriately for the purpose after measuring the acoustic characteristics. Therefore, a system that can measure the acoustic characteristic parameters of a small microphone using DSP, not only simultaneously but also in real-time, was implemented in this paper. To verify the implemented system, four kinds of microphones were measured and the results were compared with the data values of the acoustic characteristics of each microphone. There were a little discrepancy between them because the conditions when measuring the characteristics were not identical. But it was verified that the errors are within the error tolerance and it proved that the system can be used in place of the conventional equipment used in measuring the acoustic characteristics of small microphones.

• The Journal of the Acoustical Society of Korea
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• v.13 no.5
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• pp.40-50
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• 1994

In this paper, the sensitivity compensation method for three-dimensional acoustic intensity probe in the higher frequency range has been studied. The measurement error in the higher frequency range is generated from the phase mismatch between microphone's signals of the probe. If the wavelength of sound signal measured is less than those of the distance between microphones of the probe, that is, the higher frequency of the sound signal, the bigger measurement error is generated. In this study, we proposed the compensation methods for one-dimensional acoustic intensity probe with two-microphones, and the efficiency of those methods were investigated by numerical calculation of computer. It was most effective method to compensate the phase mismatch between microphone for the acoustic intensity probe was investigated for the sound estimated. and the efficiency of this method in a three-dimensional probe was investigated for the sound wave travelling in the arbitrary direction by numerical calculation of computer. In this result, the efficiency was proved that, for the measurement error of 1dB or less with the three-dimensional probe of 60mm space, the frequency should be less than 1.2kHz without the error compensation method, but the frequency increased up to 2.8kHz with the error compensation method.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.72-77
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• 2024

Recently, the necessity for sound source localization has grown significantly across various industrial sectors. Among the sound source localization methods, sound intensimetry has the advantage of having high accuracy even with a small microphone array. However, the increase in localization error at high Helmholtz numbers have been pointed out as a limitation of this method. The study proposes a method to compensate for the bias error of the measured sound intensity vector according to the Helmholtz numbers by applying deep learning. The method makes it possible to estimate the accurate direction of arrival of the source by applying a dense layer-based deep learning model that derives compensated sound intensity vectors when inputting the sound intensity vectors measured by a tetrahedral microphone array for the Helmholtz numbers. The model is verified based on simulation data for all sound source directions with 0.1 < kd < 3.0. One can find that the deep learning-based approach expands the measurement frequency range when implementing the sound intensimetry-based sound source localization method, also one can make it applicable to various microphone array sizes.

• Journal of KSNVE
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• v.11 no.1
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• pp.57-67
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• 2001

Proposed in this paper is a method of measurement of the flow rate in a pipe. The sound waves which are propagated within a pipe are characterized by that the wavenumber in the axial direction is changed according to the flow rate, and these characteristics are used in the present method of measurement of the flow rate. The amount of change in wavenumber of sound waves according to the flow rate can be obtained from the relationship among acoustic pressure signals within a pipe, which are measured by using a microphone array. The flow rate can be obtained by using the amount of change in wavenumber of sound waves and the relational equation of the flow rate. With respect to errors that can occur during the measurement of the flow rate, the types of errors and the method of correction of those errors are presented. This method of measurement of the flow rate has application limitation conditions due to the sensor interval, assumption of sound waves as plane waves, etc. The numerical simulation and experiments for measuring the flow rate of air in a pipe are performed in order to verify the applicability of this method of measurement of the flow rate. The experimental results are shown to be similar to those of the numerical simulation. And the flow rate measured is shown to be consistent with the actual value within 5% error bound.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.723-726
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• 2009

In this research, We simulated performances of error reduction algorithm for the speech signal based on the microphone array-based beamforming method in speech recognition system and analyzed its performance. Also, we processed speech signal adopted from microphone array and maximum signal to noise ratio for each channel, and then compared them with signal to noise ratio of speech signal. Speech recognition rate is improved from 54.2% to 61.4% in case 1 and is improved from 41.2% to 50.5% in case 2 of the lower signal to noise ratio. Therefore the average reduction rates are showed 15.7% in case 1.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.12
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• pp.1216-1222
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• 2010

Based on the MacDonald's analytic model for the diffracted sound field of a semi-infinite noise barrier, computer simulations were performed for various positions of error microphones for an active noise barrier system. The simulation process also included the effects of floor reflections on both sides of the barrier. The results were also compared with Niu's simulation results and showed a straight line arrangement of sensors and actuators, in the order of primary source, secondary source and error microphone is better than over the top arrangement of the error microphones.

• MALSORI
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• no.50
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• pp.111-122
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• 2004

Automatic detection of laryngeal diseases by voice is attractive because of its non-intrusive nature. Cepstrum based approach to detect laryngeal cancer shows reliable performance even when the periodicity of voice signals is severely lost, but it has a drawback that it is not robust to channel mismatch due to different microphone characteristics. In this paper, to deal with mismatched training and test microphone conditions, we investigate channel compensation techniques such as Cepstral Mean Subtraction (CMS) and Pole Filtered CMS (PFCMS). According to our experiments, PFCMS yields better performance than CMS. By using PFCMS, we obtained 12% and 40% error reduction over baseline and CMS, respectively.

• 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).

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.108-113
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• 1994

Active noise control technique has superior performance in low frequency ranges(50 .approx. 400Hz) to the conventional passive noise control technique. For the feasibility of active noise control, it is required to develop a controller which can implement control algorithm on real-time. In this study, therefore, real-time controller is developed using TMS320c25, high speed digital processor. Unlike conventional DSP board of complete ADD ON type, it is possible for the developed controller to interface with the other computer system easily by series communication for the convenience of program development. Furthermore it is designes to be separated readily as a control device. Active noise control of duct system is implemented ti evaluate a performance of developed device. Active noise control of duct system is implemented to evaluate a performance of developed controller using filtered-x LMS algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.123-129
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• 2017

This paper proposes a new nonnegative matrix factorization (NMF) based direction-of-arrival (DOA) estimation method for multiple sound sources using a dual microphone array. First of all, sound signals coming from the dual microphone array are segmented into consecutive analysis frames, and a steered-response power phase transform (SRP-PHAT) beamformer is applied to each frame so that stereo signals of each frame are represented in a time-direction domain. The time-direction outputs of SRP-PHAT are stored for a pre-defined number of frames, which is referred to as a time-direction block. Next, In order to estimate DOAs robust to noise, each time-direction block is normalized along the time by using a block subtraction technique. After that, an unsupervised NMF method is applied to the normalized time-direction block in order to cluster the directions of each sound source in a multiple sound source environments. In particular, the activation and basis matrices are used to estimate the number of sound sources and their DOAs, respectively. The DOA estimation performance of the proposed method is evaluated by measuring a mean absolute error (MAE) and the standard deviation of errors between the oracle and estimated DOAs under a three source condition, where the sources are located in [$-35{\circ}$, 5m], [$12{\circ}$, 4m], and [$38{\circ}$, 4.m] from the dual microphone array. It is shown from the experiment that the proposed method could relatively reduce MAE by 56.83%, compared to a conventional SRP-PHAT based DOA estimation method.