• 한국음향학회지
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• 제40권5호
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• pp.479-487
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• 2021

본 논문에서는 잡음 학생 모델 기반의 자가 학습을 활용한 음향 사건 검지 기법을 제안한다. 제안된 음향 사건 검지 모델은 두 단계로 구성된다. 첫 번째 단계에서는 잔차 합성곱 순환 신경망(Residual Convolutional Recurrent Neural Network, RCRNN)을 훈련하여 레이블이 지정되지 않은 비표기 데이터셋의 레이블 예측에 활용한다. 두 번째 단계에서는 세 가지 잡음 종류를 적용한 잡음 학생 모델을 자가학습 기법으로 반복하여 학습한다. 여기서 잡음 학생 모델은 SpecAugment, Mixup, 시간-주파수 이동을 활용한 특징 잡음, 드롭아웃을 활용한 모델 잡음, 그리고 semi-supervised loss function을 적용한 레이블 잡음을 활용하여 학습된다. 제안된 음향 사건 검지 모델의 성능은 Detection and Classification of Acoustic Scenes and Events(DCASE) 2020 Challenge Task 4의 validation set으로 평가하였다. DCASE 2020 챌린지 데이터셋의 baseline 및 최상위 랭크된 모델과 이벤트 단위 F1 점수 성능을 비교한 결과, 제안된 음향 사건 검지 모델이 단일 모델과 앙상블 모델에서 최상위 모델 대비 F1 점수를 각각 4.6 %와 3.4 % 향상시켰다.

• ETRI Journal
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• 제25권1호
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• pp.49-51
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• 2003

Pitch estimation is important in various speech research areas, but when the speech is noisy, accurate pitch estimation with conventional pitch detectors is almost impossible. To solve this problem, we propose a new pitch detection algorithm for noisy speech using a noise whitening technique on the background noise and obtain successful results.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅲ
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• pp.1251-1254
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• 2003

In this paper, Experience Sensitive Cumulative Neural Network (ESCNN) is introduced, which can cumulate the same or similar experiences. As the same or similar training patterns are cumulated in the network, the system recognize more important information in the training patterns. The functions of forgetting less important informations and attending more important informations resided in the training patterns are surveyed and implemented by simulations. The system behaves well under the noisy circumstances due to its forgetting and/or attending properties, even in 50 percents noisy environments. This paper also describes the creation of the generalized patterns for the input training patterns.

• ETRI Journal
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• 제30권5호
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• pp.753-755
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• 2008

In this letter, we propose a new histogram equalization technique for feature compensation in speech recognition under noisy environments. The proposed approach combines a signal-to-noise-ratio-dependent feature reconstruction method and the class histogram equalization technique to effectively reduce the acoustic mismatch present in noisy speech features. Experimental results from the Aurora 2 task confirm the superiority of the proposed approach for acoustic feature compensation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.85-88
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• 1996

We develop an efficient technique of controlling chaos using M-step ahead prediction with the OGY method. It has smaller transient time than the OGY method, and prevents burst phenomena that occur in noisy environment. This technique is very simple and needs small memory compared with targeting algorithms. Numerical examples show that the proposed algorithm has good performance, especially in noisy environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1196-1199
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• 1990

The authors proposed a new two-dimensional(2D) positioning system by use of M-array suitable for noisy environment in '88KACC and its revised version in '89KACC. This 2D positioning system is further improved to be used in practice; the computation time is improved by use of vector signal processor and the focussing process is improved by use of an electrically controlled zoom lense. It is shown that this system is robust to noise and also to misalignment of devices.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제21권1호
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• pp.29-37
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• 2017

A general optimal recovery problem is to approximate a value of a linear operator on a subset (class) in linear space from a value of another linear operator (called information), measured with an error in given metric. We use this formulation to investigate the classical computerized tomography problem of inversion of the noisy Radon transform.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제7권1호
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• pp.47-61
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• 2003

Two principally different statements of the problem of stable numerical differentiation are considered. It is analyzed when it is possible in principle to get a stable approximation to the derivative ${\Large f}'$ given noisy data ${\Large f}_{\delta}$. Computational aspects of the problem are discussed and illustrated by examples. These examples show the practical value of the new understanding of the problem of stable differentiation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.397-400
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• 2002

This paper has been studied speech enhancement method in noisy environment. By mean of that we prefer human auditory mechanism which is perfect system and applied wavelet transform. Multi-resolution of wavelet transform make possible multiband spectrum analysis like human ears. This method was verified very effective way in noisy speech enhancement.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.365-366
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• 2006

This paper describes a pre-processing methodology which can apply to remote speech recognition system of service robot in noisy environment. By combining beamforming and blind source separation, we can overcome the weakness of beamforming (reverberation) and blind source separation (distributed noise, permutation ambiguity). As this method is designed to be implemented with hardware, we can achieve real-time execution with FPGA by using systolic array architecture.