• 대한음성학회지:말소리
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• 제60호
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• pp.181-190
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• 2006

This paper describes a speech enhancement scheme that leads to significant improvements in recognition performance when used in the ASR front-end. The proposed approach is based on adaptive comb filtering and an MMSE-related parameter estimator. While adaptive comb filtering reduces noise components remarkably, it is rarely effective in reducing non-stationary noises. Furthermore, due to the uniformly distributed frequency response of the comb-filter, it can cause serious distortion to clean speech signals. This paper proposes an improved comb-filter that adjusts its spectral magnitude to the original speech, based on the speech absence probability and the gain modification function. In addition, we introduce the modified comb filtering-based speech enhancement scheme for ASR in mobile environments. Evaluation experiments carried out using the Aurora 2 database demonstrate that the proposed method outperforms conventional adaptive comb filtering techniques in both clean and noisy environments.

• ETRI Journal
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• 제25권1호
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• pp.52-54
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• 2003

We propose an improved algorithm for detecting audio watermarks based on a spread spectrum in the spectral domain. Since the energy of a watermark is much smaller than that of the cover audio data, pre-processing to reduce the effect of the cover data is needed to reliably extract watermarks. We introduce a spectral envelope filter as a pre-process that enhances detecting performance by filtering out the intrinsic spectral character of cover data. The proposed watermarking structure can be easily included in the compression system and can extract watermarks from partially decompressed spectral data. Our experimental results demonstrate that with a bit error rate of around 10 dB against general attacks, the proposed detecting scheme works better than detectors without the spectral filter.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권9호
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• pp.547-553
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• 2003

In this paper, we designed the PC-based analyzer of the power spectral density that could estimate the heart rate variability from time series data of R-R interval. The power spectral density estimated that it applied the autoregressive model to the measured electrocardiogram during a short period. Also, the characteristics of the designed analyzer are that it could process of the signal filtering, the generation and recomposition of time series and the feature extraction at the same time. Especially the analyzer reconstructed which applied the lowpass filter of the time series composed by the linear interpolation so as to enhance the signal-to-noise feature. We could estimate the power spectral density that confirmed a variety of power peak with low frequency range and high frequency rang of autonomic nerve by the heart rate variability.

• Journal of the Optical Society of Korea
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• 제13권3호
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• pp.354-360
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• 2009

We investigate theoretically the tolerance of 40 Gbps phase-modulated (PM) duobinary signals using a vestigial sideband (VSB) filter on impairments which occurred in dense wavelength-division multiplexing (DWDM) systems, compared to the conventional duobinary signals. Our simulation results show that PM duobinary signals can't have the gain on the spectral efficiency achieved by utilizing the VSB filtering technique. In order to increase the spectral efficiency, they indispensably require to be transmitted at the optimum bandwidth of multiplexer (MUX) and demultiplexer (DEMUX) since they are susceptible to inter-channel crosstalk. It is also shown that the PM duobinary modulation format has a large tolerance on self-phase modulation (SPM) and cross-phase modulation (XPM) under the condition which MUX and DEMUX have been tuned at an optimum bandwidth; it has 1.2 dB power penalty at the fiber launching power (FLP) of 15 dBm and the channel spacing of 50 GHz.

• 대한원격탐사학회지
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• 제19권5호
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• pp.351-361
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• 2003

As the launches of a series of remote sensing satellites, there are various multiresolution and multi-spectral images available nowadays. This diversity in remotely sensed image data has created a need to be able to integrate data from different sources. The C-band imaging radar of ERS-2 due to its high sensitivity to coastal wetlands holds tremendous potential in mapping and monitoring coastal wetland features. This paper investigates the advantages of using ERS-2 SAR data combined with IRS-ID LISS-3 data for mapping complex coastal wetland features of Tamil Nadu, southern India. We present a methodology in this paper that highlights the mapping potential of different combinations of filtering and integration techniques. The methodology adopted here consists of three major steps as following: (i) speckle noise reduction by comparative performance of different filtering algorithms, (ii) geometric rectification and coregistration, and (iii) application of different integration techniques. The results obtained from the analysis of optical and microwave image data have proved their potential use in improving interpretability of different coastal wetland features of southern India. Based visual and statistical analyzes, this study suggests that brovey transform will perform well in terms of preserving spatial and spectral content of the original image data. It was also realized that speckle filtering is very important before fusing optical and microwave data for mapping coastal mangrove wetland ecosystem.

• 정보보호학회논문지
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• 제10권4호
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• pp.13-19
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• 2000

정보 통신 기술의 급속한 발달로 인해 웹 상에서 멀티미디어 데이터 및 전자적인 공문서는 점점 더 확산되고 있고, 이런 디지털화 된 정보에 대한 소유권 보호 및 인증의 필요성이 요구되고 있는 실정이다. 본 논문에서는 직교 웨이브릿 변환을 이용하여 각 계층의 주파수 영역에 잘 적응하는 다중 워터마크를 내장하는 적응성 스펙트럼 워터마크 알고리즘 을 제안한다. 실험결과 low-Pass fitering, bluring, sharpen filtering, 웨이브릿 압축과 같은 영상 변형뿐만 아니라 brightness, contrast, gamma correction, histogram equalization. cropping과 같은 영상의 변형에 강인한 워터마크 영상을 생성시켰다

• 한국전자통신학회논문지
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• 제5권4호
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• pp.363-371
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• 2010

특징벡터의 분류를 개선시켜 화자독립 음성인식의 오류율을 줄이려는 노력의 일환으로서, 우리는 MFCC의 추출에 있어서 푸리에 스펙트럼을 기울이는 방법이 미치는 효과를 연구한다. 음성신호에 FIR 필터링을 적용하는 효과의 조사도 병행된다. 제안된 방법은 두 가지 독립적인 방법에 의해 평가된다. 즉, 피셔의 차별함수에 의한 방법과 은닉 마코브 모델 및 퍼지 벡터양자화를 사용한 음성인식 오류율 조사 방법이다. 실험 결과, 적절한 파라미터의 선택에 의해 기존의 방법에 비해 10% 정도 낮은 인식 오류율이 얻어짐을 확인하였다.

• The Journal of the Acoustical Society of Korea
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• 제23권2E호
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• pp.56-67
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• 2004

Despite abundant research outcomes of blind source separation (BSS) in many types of simulated environments, their performances are still not satisfactory to be applied to the real environments. The major obstacle may seem the finite filter length of the assumed mixing model and the nonlinear sensor noises. This paper presents a two-step speech enhancement method with multiple microphone inputs. The first step performs a frequency-domain BSS algorithm to produce multiple outputs without any prior knowledge of the mixed source signals. The second step further removes the remaining cross-channel interference by a spectral cancellation approach using a probabilistic source absence/presence detection technique. The desired primary source is detected every frame of the signal, and the secondary source is estimated in the power spectral domain using the other BSS output as a reference interfering source. Then the estimated secondary source is subtracted to reduce the cross-channel interference. Our experimental results show good separation enhancement performances on the real recordings of speech and music signals compared to the conventional BSS methods.

• 한국항행학회논문지
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• 제21권3호
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• pp.243-250
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• 2017

GPS 신호체계는 대역확산 방식을 사용하며, 신호의 크기는 시스템 잡음수준 이하이므로 외부 전파 간섭신호에 매우 취약하며, 이는 GPS를 이용하는 선박 또는 항공기 에 대한 안전 운항을 제한 할 수 있다. 본 논문은 이러한 GPS 간섭 신호 제거를 위한 K-median 방식의 문턱치 설정 방식을 적용한 주파수 영역의 신호 처리 기법을 제안하며, 이는 기존에 보편적으로 사용되는 시간 영역에서의 간섭신호 제거 방식보다, 시간에 따른 신호 변화가 큰 간섭신호를 인가한 조건에 대해서 상대적으로 우수한 성능을 가짐을 확인하였다.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.748-764
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• 2019

In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.