• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.295-298
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• 2004

본 논문에서는 잡음에 오염된 신호의 지각관계를 해석하여 지각 필터 응답 제어를 통한 음성 신호 개선 알고리즘을 제안한다. 음성 신호 개선 기법은 단일 채널환경에서 사람의 청각시스템에서의 주파수 변별력을 나타내는 각각의 임계대역에 대한 전체 에너지를 나타내는 임계대역 에너지의 지각적인 확산의 영향 즉, 마스킹 확산의 영향을 나타내는 자극에너지를 이용하여 신호와 잡음 에너지에 의해 변화하는 잡음에 의한 신호의 마스킹 구간을 검출하여 묵음 구간 추출 잡음 필터응답과 추정 잡음 오차를 보상시킨 필터응답을 통한 지각 필터 응답을 보상하여 신호를 개선하는 방법이다. 실험 결과 제안한 방법을 통해 SNR에 개선과 음질 개선 효과를 얻을 수 있음을 테스트를 통해 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.335-337
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• 2018

음성향상기법은 음성에 포함된 잡음이나 잔향을 제거하는 기술로써 마이크로폰으로 입력된 음성신호는 잡음이나 잔향에 의해 왜곡되어지므로 음성인식, 음성통신 등의 음성신호처리 기술의 핵심 기술이다. 이전에는 음성신호와 잡음신호 사이의 통계적 정보를 이용하는 통계모델 기반의 음성향상기법이 주로 사용되었으나 통계 모델 기반의 음성향상기술은 정상 잡음 환경과는 달리 비정상 잡음 환경에서 성능이 크게 저하되는 문제점을 가지고 있었다. 최근 머신러닝 기법인 심화신경망 (DNN, deep neural network)이 도입되어 음성 향상 기법에서 우수한 성능을 내고 있다. 심화신경망을 이용한 음성 향상 기법은 다수의 은닉 층과 은닉 노드들을 통하여 잡음이 존재하는 음성 신호와 잡음이 존재하지 않는 깨끗한 음성 신호 사이의 비선형적인 관계를 잘 모델링하였다. 이러한 심화신경망 기반의 음성향상기법을 향상 시킬 수 있는 방법 중 하나인 강화학습을 적용하여 기존 심화신경망 대비 성능을 향상시켰다. 강화학습이란 대표적으로 구글의 알파고에 적용된 기술로써 특정 state에서 최고의 reward를 받기 위해 어떠한 policy를 통한 action을 취해서 다음 state로 나아갈지를 매우 많은 경우에 대해 학습을 통해 최적의 action을 선택할 수 있도록 학습하는 방법을 말한다. 본 논문에서는 composite measure를 기반으로 reward를 설계하여 기존 PESQ (Perceptual Evaluation of Speech Quality) 기반의 reward를 설계한 기술 대비 음성인식 성능을 높였다.

• 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.121-128
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• 2005

On the research field for speech signal, neural network mainly uses for the category classification in speech recognition and applies to signal processing. Accordingly, this paper proposes a noise reduction system using a time-delay neural network, which implements the mapping from the space of speech signal degraded by noise to the space of clean speech signal. It is confirmed that this method is effective for speech degraded not only by white noise but also by colored noise using the noise reduction system, which restores the amplitude component of fast Fourier transform.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7B
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• pp.1270-1281
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• 2000

본 논문에서는 수신신호의신호대잡음비를 이용하여 작동되는 적응부호화 시스템을 레일레이 페이딩 채널 환경에서 분석한다. 분석에서는 레일레이 페이딩 채널을 수신신호의 신호대잡음비를 K개의 구간으로 나누어서 유한 상태 마르코프 채널로 모델링한다. 채널 상태를 예측하는 과정에서 발생하는 오류확률을 고려하여 적응부호화 시스템의 평균 BER과 throughput이 계산된다. 본 논문에서 제안한 분석 방법을 이용하여 천공 길쌈부호를 이용한는 적응부호화 시스템의 성능을 분석한 결과가 예제로 보여진다.

• The Journal of the Acoustical Society of Korea
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• v.34 no.2
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• pp.163-170
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• 2015

In this paper, it is shown that the performance of the frequency-domain multi-reference narrowband noise canceller is determined by the narrowband component to the broadband disturbance power ratio in the reference signals. To overcome this problem, a new narrowband ANC is proposed, where the update of the adaptive filter is determined based on SNR of the reference inputs being measured using the magnitude squared coherence (MSC) between the primary and the reference signals. Simulation results show that the proposed ANC has superior performance over the conventional one.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.33-38
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• 2005

Degradation is generated by several causes in the process of digitalization or transmission of data. And its essential cause is noise. Therefore, researches for wavelet-based methods which reconstruct signal degraded by noise have continued. In AWGN(addtive white gaussian noise) environment, the general trend for denoising is to use the thresholding method. Reconstructed signal includes a lot of noise because these methods only consider statistical characteristic regarding noise. In this paper, we present a new method which uses the cumulation of wavelet detail coefficients. As a result, reconstruction of edges and denoising performance are improved. Also we compare existing methods using SNR(signal-to-noise ratio) as the standard of judgement of improvemental effect.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.687-693
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• 2003

In this paper, a new adaptive audio signal enhancement algorithm is proposed. In order to remove a broadband noise from a noisy signal, a filter is designed and applied adaptively to noisy audio signal. The noisy signal is first transformed to frequency domain and divided into bark domain to calculate excitation energy. A filter will be calculated to eliminate the noise by using the excitation energy and noisy energy which is obtained from a silent area. The filter is adaptively adjusted and continuously applied until the threshold point is met. The algorithm also works well even though the noise's energy change all of a sudden. SNR, NMR comparison and MOS Test are performed to show the effectiveness of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9A
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• pp.678-683
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• 2003

The pseudo-noise (PN) code acquisition based on the sequential estimation (SE) proposed by Ward performs well only at relatively high chip signal-to-noise ratios (SNRs). In this paper, a seed accumulating sequential estimation (SASE) method and a PN code acquisition system based on it are proposed, which perform well at low chip SNR (of practical interest) also. Then, the mean acquisition time performance of the proposed system is investigated. Numerical results show that the system based on the SASE performs dramatically better than that based on the SE at low chip SNR, and the improvement becomes larger as the period of PN code increases.

• Aerospace Engineering and Technology
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• v.8 no.1
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• pp.58-65
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• 2009

The paper identifies noise characteristics of a nonliner image sensor model which reflects a saturation effect of each detector pixel and extends the result to estimate an image SNR (Signla-to-Noise Ratio) distribution over all the pixels in a detector. In particular, nonlinearity of a pixel is studied from two perspectives of including asymmetry of a noise PDF (Probability Distribution Function) and enhancing a pixel SNR value, in comparison to a linear model. It is noted that the proposed image SNR distribution function is useful to effectively select new optimal operation parameter values: an integration time and an pixel-summing number, even after a launch campaign, assuming sensor gain degradation in orbit or inevitable modification of some operation parameter values due to space contingency.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.159-168
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• 2019

We examined the effect of Siemens ADMIRE (Advanced Modeled Iterative Reconstruction) on image quality by measuring changes in HU, noise, and SNR of background air, fat, muscle, and background signals on a chest CT scan. Experimental results show that as the ADMIRE Strength increases, the noise decreases and the signal increases, consequently the signal-to-noise ratio increases. ADMIRE can reduce noise by 28 ~ 61% compared to FBP, which is a conventional image reconstruction algorithm, and improves SNR by 16 ~ 100%.