• The Journal of the Acoustical Society of Korea
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• v.29 no.2E
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• pp.86-99
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• 2010

This paper analyzes the performance of various single channel speech enhancement algorithms when they are applied to automatic speech recognition (ASR) systems as a preprocessor. The functional modules of speech enhancement systems are first divided into four major modules such as a gain estimator, a noise power spectrum estimator, a priori signal to noise ratio (SNR) estimator, and a speech absence probability (SAP) estimator. We investigate the relationship between speech recognition accuracy and the roles of each module. Simulation results show that the Wiener filter outperforms other gain functions such as minimum mean square error-short time spectral amplitude (MMSE-STSA) and minimum mean square error-log spectral amplitude (MMSE-LSA) estimators when a perfect noise estimator is applied. When the performance of the noise estimator degrades, however, MMSE methods including the decision directed module to estimate a priori SNR and the SAP estimation module helps to improve the performance of the enhancement algorithm for speech recognition systems.

• Journal of Satellite, Information and Communications
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• v.5 no.1
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• pp.1-5
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• 2010

Recently, the transmission amount of information that each single person requires is growing by development of electron information communication technology. So in this paper we analysis the phase noise characteristics to obtain a most suitable of SNR performance request characteristic by BER on CATV transmission system that satisfy performance request DOCSIS 2.0 standard. Especially we get the parameter value of PLL that satisfy phase noise characteristic request standard using developed simulator. Presented method can be used to obtain a performance request standard connection performance request standard of high speed CATV transmission system in the future.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.366.1-366
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• 2002

It is addressed that the turbulent broadband sound power from a sirocco fan can be modeled by the trailing edge noise. The trailing edge noise is usually influenced by inflow turbulence, separation, and boundary layer on the blade. The design parameters such as solidity(c/s) and stagger angle are specified to predict performance and noise level because the separation and slip velocity are strong1y affected by them along with the flow coefficient. (omitted)

• The Journal of the Acoustical Society of Korea
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• v.21 no.2
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• pp.134-141
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• 2002

In this paper, a free wake analysis based on the curved vortex element and CVC wake model is used to predict the aerodynamic performance and noise for HAWT. Also for prediction of RPM, a maximum value through a quadratic regression was suggested. And for a noise prediction, the broadband noise prediction method based on experimental equation was used. The curved vortex element uses a BCVE and an SIVE instead of a straight vertex element. In the CVC wake model, the vortex strengths are assumed to be constant along a span and a vortex filament. The free wake structure made by the curved vortex element and CVC was substituted for a vortex lattice, so it has an advantage for the less calculation time and a depiction of accurate wake structure. For the verification of this program, calculated results are compared with Mr. Kim's experiment model and Zond Z-40FS for performance and with WTS-4 and USWP models for noise. Good agreements are obtained between the predicted and the measured data for the performance and far-field noise spectra.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.4
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• pp.271-276
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• 2021

Arc fault detector based on multilevel DWT with analysis of high-frequency noise components over 100 kHz is proposed in this study to improve the performance in detecting serial arcs and distinguishing them from inverter noise in PV systems. PV inverters generally operate at a frequency range of 20-50 kHz for switching operation and maximum power tracking control, and the effect of these frequency components on the signal for arc detection leads to negative arc detection. High-speed ADC and multilevel DWT are used in this study to analyze frequency components above 100 kHz. Such high frequency components are less influenced by inverter noise and utilized to detect as well as separate DC series arc from inverter noise. Arc detectors identify the input current of PV inverters using a Rogowski coil. The sensed signal is filtered, amplified, and used in 800kSPS ADC and DWT analysis and arc occurrence determination in DSP. An arc detection simulation facility in UL1699B was constructed and AFD tests the proposed detector were conducted to verify the performance of arc detection and performance of distinction of the negative arc. The satisfactory performance of the arc detector meets the standard of arc detection and extinguishing time of UL1699B with an arc detection time of approximately 0.11 seconds.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.113-118
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• 2024

In this paper, we propose an optimal wavelet in a system for canceling background noise of acoustic signals. This system performed Discrete Wavelet Transform(DWT) instead of the existing Short Time Fourier Transform(STFT) and then improved noise cancellation performance through a deep learning process. DWT functions as a multi-resolution band-pass filter and obtains transformation parameters by time-shifting the parent wavelet at each level and using several wavelets whose sizes are scaled. Here, the noise cancellation performance of several wavelets was tested to select the most suitable mother wavelet for analyzing the speech. In this study, to verify the performance of the noise cancellation system for various wavelets, a simulation program using Tensorflow and Keras libraries was created and simulation experiments were performed for the four most commonly used wavelets. As a result of the experiment, the case of using Haar or Daubechies wavelets showed the best noise cancellation performance, and the mean square error(MSE) was significantly improved compared to the case of using other wavelets.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.880-881
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• 2009

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.595-595
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• 2008

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.196-197
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• 2012

• Proceedings of the KSR Conference
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• 2002.05a
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• pp.584-589
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• 2002

Recently, in various industrial field standardization and performance improvement are actively on going. Noise barrier is generally used to reduce railway noise. But the effectiveness of its use is low because of low level of technology development. In this basic study, test item and its specification are suggested for standardization of railway noise barrier.