• The Journal of the Acoustical Society of Korea
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• v.22 no.2E
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• pp.87-92
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• 2003

In this paper, a new speech enhancement method using level adapted wavelet packet is presented. First, we propose a level adapted wavelet packet to alleviate a drawback of the conventional node adapted one in noisy environment. Next, we suggest an adaptive noise estimation method at each node on level adapted wavelet packet tree. Then, for more accurate noise component subtraction, we propose a new estimation method of spectral subtraction weight. Finally, we present a modified spectral subtraction method. The proposed method is evaluated on various noise conditions: speech babble noise, F-l6 cockpit noise, factory noise, pink noise, and Volvo car interior noise. For an objective evaluation, the SNR test was performed. Also, spectrogram test and a very simple listening test as a subjective evaluation were performed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.496-499
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• 2008

The noise reducing devices installed on the noise barrier have been developed in many shapes and ways to reduce noise around road traffic areas. In this study, test and estimation method for the noise reducing device witch installed on the top of a noise barrier was suggested. For this, the authors have considered sound power flow around the device and sound pressure levels for the far field area. To estimate the area effect behind the barrier, area average of noise pressure level difference divided by two area, upper and bellow the sight-line. Comparing the attenuation difference of these areas, the tendency of noise reduction effect was studied according to type of noise reducing devices. Compared with noise shielding efficiency of the devices that using equivalent height of a simple barrier calculated by the SoundPlan, the commercial environment noise simulation software.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1129-1134
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• 2006

Mass estimation was derived as functions of acceleration magnitude and primary frequency. The conventional method of mass estimation used frequency data directly in the frequency domain. The signals that can be obtained sensor contained noise as well as impact signal. Therefore, how well we can detect the frequency data in noise directly determines the quality of mass estimation. To find exact frequency data, we used time-frequency analysis. The time frequency method are expected to be more useful than the conventional frequency domain analyses for the mass estimation problem on a plate type structure. Also it has been concluded that the smoothed WVD can give more reliable means than the other methodologies for the mass estimation in a noisy environment.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.8 s.113
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• pp.872-878
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• 2006

Mass estimation was derived as functions of acceleration magnitude and primary frequency. The conventional method of mass estimation used frequency data directly in the frequency domain. The signals that can be obtained sensor contained noise as well as impact signal. Therefore, how well we can detect the frequency data in noise directly determines the quality of mass estimation. To find exact frequency data, we used time-frequency analysis. The time-frequency methods are expected to be more useful than the conventional frequency domain analyses for the mass estimation problem on a plate type structure. Also it has been concluded that the smoothed WVD can give more reliable means than the other methodologies for the mass estimation in a noisy environment.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.580-584
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• 2011

Sound power is one of the most significant factors to predict and assess noise from sound source. However, many researchers developed indirect methods to calculate the sound power with noise level because it is impossible to measure sound power directly while a train is running. In this paper, we proposes a method to estimate separately each sound power for rolling noise and propulsive noise with the noise emitted from rolling stocks and verifies the validity of the estimation method using other sound power estimation formula.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1926-1933
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• 2022

Parameterized multichannel Wiener filter (PMWF) is a linear filter that can control the trade-off between residual noise and signal distortion using the embedded parameter. To apply the PMWF to noisy inputs, accurate noise estimation is important and multichannel minima-controlled recursive averaging (MMCRA) is widely used. However, in the case of the MMCRA, the accuracy of noise estimation decreases when a directional interference is involved into the array inputs. Consequently, the performance of the PMWF is degraded. Therefore, we propose a noise power spectral density (PSD) estimation method for the PMWF in this paper. The proposed method is based on a consecutive process of eigenvalue decomposition on noisy input PSD, estimation of the target component contribution using directional information, and exponential weighting for improved estimation of the target contribution. For evaluation, four objective measures were compared with the MMCRA and we verify that the PMWF with the proposed noise estimation method can improve performance in environments where directional interfereces exist.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.85-95
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• 1995

The error intensity models for the ML estimation of a signal parameter have been developed in a companion paper [1]. While the methods described in [1] are applicable to any estimation problem with continuous parameters, our main application in this paper is the time delay estimation, and comparisons among the models derived in [1] (i.e. LC, LM, and ALM models)have been made. We first consider the case where only additive Gaussian noise is involved, and then the shot noise environment where coherent impulsive noise is also involved in addition to the Gaussian noise. We compare the models in terms of the probability of error, MSE(Mean Squared Error), and the computational complexity, which are the most important performance criteria in the analysis of parameter estimation. In conclusion, the ALM model turned out to be the most adequate model of all from the viewpoints of the criteria mentioned above.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.129-136
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• 2005

To reduce the noise in the noisy speech, it is desirable to change the parameters of the speech processing system according to the noise intensity to reproduce a good quality speech. This paper proposes an estimation method of noise intensity using a three layered neural network, which is able to learn the three graded speeches that is degraded by white noise or road noise. Experimental results demonstrate that the noise intensity could be estimated by the neural network. Even if the speakers and speech data are different from the training data, estimation rates for the noise intensity can be estimated by the neural network with an average accuracy of $95\%$ or more for white noise.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.41-51
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• 2014

This paper describes a method to estimate the noise power using the minimum statistics approach, which was originally proposed for audio processing. The proposed minimum statistics-based method separates a noisy image into multiple frequency bands using the three-level discrete wavelet transform. By assuming that the output of the high-pass filter contains both signal detail and noise, the proposed algorithm extracts the region of pure noise from the high frequency band using an appropriate threshold. The region of pure noise, which is free from the signal detail part and the DC component, is well suited for minimum statistics condition, where the noise power can be extracted easily. The proposed algorithm reduces the computational load significantly through the use of a simple processing architecture without iteration with an estimation accuracy greater than 90% for strong noise at 0 to 40dB SNR of the input image. Furthermore, the well restored image can be obtained using the estimated noise power information in parametric image restoration algorithms, such as the classical parametric Wiener or ForWaRD image restoration filters. The experimental results show that the proposed algorithm can estimate the noise power accurately, and is particularly suitable for fast, low-cost image restoration or enhancement applications.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.612-617
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• 2009

In a DCT coding, degradations called block artifact and mosquito noise are appeared in reconstructed pictures. They should be reduced in post processing after decoding without superabundant processing. However, an estimation of mosquito noise is rare because of its difficulty. To realize an estimation of mosquito noise level, we extract a block that mosquito noise will be easy to occur. Mosquito noise level is calculated at a selected side of the block. In this processing, only the sides of high probability block are used. Then, a block value is taken by averaging. Finally, the picture value is calculated by averaging of this. Estimation method is evaluated by using the MPEG-4 decoded pictures. Quantization scale of coding and the estimated mosquito noise level are compared. As the results, we recognize the proposed method gives almost reasonable mosquito block and absolute level. Father, adaptive filter is controlled by the estimated mosquito noise level. It is recognized that the high quality of decoded picture is kept and the mosquito noise is reduced effectively at the picture with degradation.