• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.10a
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• pp.86-91
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• 1995

음원의 위치를 찾는 문제에 있어서 비독립 음원들이 존재하는 경우, 근접장에서는 음원으로부터 나오는 파형을 평면파로 가정할 수 없고 구면파로 가정해야 하며, 여러개의 비독립 음원이 존재한다고 가정하여 각각의 음원의 위치를 변화시켜 가면서 MUSIC파워를 계산하여야 한다. 실제 음원의 갯수보다 가정한 음원의 갯수가 작으면 정확한 음원의 위치를 가르키지 못하며 MUSIC 파워 값도 작다. 실제 음원의 갯수와 가정한 음원의 갯수가 같으면 정확한 음원의 위치를 가르치며 MUSIC 파워 값이 크게 얻어진다. 실제 음원의 갯수보다 가정한 음원의 갯수가 큰 경우 실제의 음원의 위치를 포함하여 다른 음원의 위치를 얻을 수 있으나 그 음원의 세기는 무시할 정도로 작다. 즉 실제 음원의 갯수보다 많은 수의 음원을 가정하여 음원을 탐지할 수 있다. 일반 음장 즉 독립 음원과 비독립 음원이 공존하는 경우 실제의 음원의 갯수만큼 가정한다면 음원이 위치를 찾을 수 있다.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.807-812
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• 2020

This paper proposes a blind speech source separation algorithm using a microphone to separate only the target speech source signal in an environment in which various speech source signals are mixed. The proposed algorithm is a model of frequency domain representation based on independent component analysis method. Accordingly, for the purpose of verifying the validity of independent component analysis in the frequency domain for two speech sources, the proposed algorithm is executed by changing the type of speech sources to perform speech sources separation to verify the improvement effect. It was clarified from the experimental results by the waveform of this experiment that the two-channel speech source signals can be clearly separated compared to the original waveform. In addition, in this experiments, the proposed algorithm improves the speech source separation performance compared to the existing algorithms, from the experimental results using the target signal to interference energy ratio.

• Journal of KSNVE
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• v.6 no.6
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• pp.835-842
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• 1996

To identify the locations and strengths of acoustic sources, one may use a microphone line array. Apparent advantage of the source identification method utilizing a line array is that it requires less measurement points than intensity method and holography. This method is based on the information of magnitude and phase difference between pressure signals at each microphone. Since those differences are dependent on the source model, we have to assume them such as plane, monopole, etc. In this paper the conventional source identification methods such as beamforming method and MUSIC method are briefly reviewed by modeling a source as plane and spherical wave, then a modified method is introduced. This can be applied to sound field which may by either coherent or incoherent. Typical simulations and experiment are performed to confirm this identification method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.2
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• pp.77-82
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• 2011

In this paper, we investigate source separation algorithms for stereo audio mixed using amplitude panning method. This source separation algorithms can be used in various applications such as up-mixing, speech enhancement, and high quality sound source separation. The methods in this paper estimate the panning angles of individual signals using the principal component analysis being applied in time-frequency tiles of the input signal and independently extract each signal through directional filtering. Performances of the methods were evaluated through computer simulations.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.266-269
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• 2010

급속한 정보 통신 기술의 발달로 인해 멀티미디어 재생 개발 기술들은 단순히 수동적으로 보고 듣는 재생 기술에서 벗어나 청취자 감성, 취향 등에 따라 보다 실감 있고 사용자가 능동적으로 재생할 수 있는 기술로 진화 하고 있다. 지금까지의 오디오 서비스는 음원 개발자 중심의 오디오 서비스, 즉 보컬 및 모든 악기가 믹스된 단일음원이기 때문에 사용자는 단순히 오디오 음원 개발자나 음반 제작사가 발매한 단일 음원을 일방적으로 수동적 청취할 수밖에 없다. 하지만 사용자 능동형 오디오 서비스에서는 사용자가 능동적으로 자신이 원하는 음악적 취향에 따라 능동적으로 각각의 객체 기반의 독립 음원을 선택, 감성에 따른 음원 효과 추가, 최적의 음원 청취 위치(Sweet Spot) 변경, 음원 및 스피커 재생 공간 및 위치 변경 재생 등을 할 수가 있다. 본 논문에서는 디지털 음원들을 입력받아 임의의 필터링을 실행하고, 사용자 음원 보정 정보, 출력 유닛의 공간적, 음향적 특성을 상위제어기로부터 입력받아 전신호경로 상에 디지털 신호처리 하여 출력신호를 생성하는 DSP 시스템 플랫폼 및 알고리즘에 관하여 소개한다.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.35-41
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• 2016

Based on correlation and least square method, a closed-form algorithm for estimating the location of mixed far-field and near-field source is presented using the Uniform Circular Array (UCA). Recently, for a homogeneous circular arrangement case, a correlation based closed-form algorithm is proposed to estimate 2-D angle (azimuth, elevation) and the extended algorithm is proposed to 3-D location (azimuth, elevation, range). These algorithms assume the far-field source or near-field source only. Therefore, for mixed source localization, the proposed algorithm estimates source location with the assumption of far-field source, and then estimates the range to distinguish the far-field from the near-field source. For both cases, numerical experiments have been performed, which confirmed the validity of the proposed algorithm.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.328-335
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• 2005

This paper proposes a frequency domain independent component analysis (ICA) algorithm to separate the mixed speech signals using a multiple microphone array By estimating the delay timings using a input cross-correlation, even in the delayed mixture case, we propose a good initial value setting method which leads to optimal convergence. To reduce the calculation, separation process is performed at frequency domain. The results of simulations confirms the better performances of the proposed algorithm.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.889-899
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• 2017

Independent component analysis is a multivariate approach to separate mixed signals into original signals. It is the most widely used method of blind source separation technique. ICA uses linear transformations such as principal component analysis and factor analysis, but differs in that ICA requires statistical independence and non-Gaussian assumptions of original signals. PCA have a natural ordering based on cumulative proportion of explained variance; howerver, ICA algorithms cannot identify the unique optimal ordering of the components. It is meaningful to set order because major components can be used for further analysis such as clustering and low-dimensional graphs. In this paper, we compare the performance of several criteria to determine the order of the components. Kurtosis, absolute value of kurtosis, negentropy, Kolmogorov-Smirnov statistic and sum of squared coefficients are considered. The criteria are evaluated by their ability to classify known groups. Two types of data are analyzed for illustration.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.280-282
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• 2006

저장매체의 대용량화와 인터넷을 이용한 디지털 음원의 활성화로 개인이 소유하는 음원이 급속도로 증가하고 있다. 많은 양의 음원을 보유하고 있는 상황에서 사용자의 편의를 증가시키기 위하여 다양한 검색/분류 방법들이 개발되고 사용되고 있다. 본 논문에서는 음원에 사용된 표현방식이나 디렉토리 구조, 파일이름, 텍스트 태그 등에 독립적으로 적용될 수 있도록 디지털 신호처리 이론에 기반하여 파형데이터를 분석하고, 화성학 이론에 기반한 패턴매칭 기술을 응용하여 음악의 장르와 나아가 분위기를 기반으로 분류하는 방법을 제시한다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.91-99
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• 2010

Recently, recognizing user resource for personalized service has been needed in digital content service fields. Especially, to analyze user taste, recommend music and service music related information need recognition of user music file in case of online music service. Music related information service is offered through recognizing user music based on tag information. Recognition error has grown by weak points like changing and removing of tag information. Techniques of content based user music recognition with music signal itself are researched for solving upper problems. In this paper, we propose user music recognition on the internet by extracted feature from music signal. Features are extracted after suitable preprocessing for structure of content based user music recognition. Recognizing on music server consist of feature form are progressed with extracted feature. Through this, user music can be recognized independently of tag data. 600 music was collected and converted to each 5 music qualities for proving of proposed recognition. Converted 3000 experiment music on this method is used for recognition experiment on music server including 300,000 music. Average of recognition ratio was 85%. Weak points of tag based music recognition were overcome through proposed content based music recognition. Recognition performance of proposed method show a possibility that can be adapt to online music service in practice.