• Title/Summary/Keyword: 일반화된 상호상관법

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Factors for Speech Signal Time Delay Estimation (음성 신호를 이용한 시간지연 추정에 미치는 영향들에 관한 연구)

  • Kwon, Byoung-Ho;Park, Young-Jin;Park, Youn-Sik
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.8
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    • pp.823-831
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    • 2008
  • Since it needs the light computational load and small database, sound source localization method using time delay of arrival(TDOA method) is applied at many research fields such as a robot auditory system, teleconferencing and so on. Researches for time delay estimation, which is the most important thing of TDOA method, had been studied broadly. However studies about factors for time delay estimation are insufficient, especially in case of real environment application. In 1997, Brandstein and Silverman announced that performance of time delay estimation deteriorates as reverberant time of room increases. Even though reverberant time of room is same, performance of estimation is different as the specific part of signals. In order to know that reason, we studied and analyzed the factors for time delay estimation using speech signal and room impulse response. In result, we can know that performance of time delay estimation is changed by different R/D ratio and signal characteristics in spite of same reverberant time. Also, we define the performance index(PI) to show a similar tendency to R/D ratio, and propose the method to improve the performance of time delay estimation with PI.

Real-Time Sound Localization System For Reverberant And Noisy Environment (반향음과 잡음 환경을 고려한 실시간 소리 추적 시스템)

  • Kee, Chang-Don;Kim, Ghang-Ho;Lee, Taik-Jin
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.3
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    • pp.258-263
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    • 2010
  • Sound localization algorithm usually adapts three step process: sampling sound signals, estimating time difference of arrival between microphones, estimate location of sound source. To apply this process in indoor environment, sound localization algorithm must be strong enough against reverberant and noisy condition. Additionally, calculation efficiency must be considered in implementing real-time sound localization system. To implement real-time robust sound localization system we adapt four low cost condenser microphones which reduce the cost and total calculation load. And to get TDOA(Time Differences of Arrival) of microphones we adapt GCC-PHAT(Generalized Cross Correlation-Phase Transform) which is robust algorithm to the reverberant and noise environment. The position of sound source was calculated by using iterative least square algorithm which produce highly accurate position data.

Sound Source Localization Method Using Spatially Mapped GCC Functions (공간좌표로 사상된 GCC 함수를 이용한 음원 위치 추정 방법)

  • Kwon, Byoung-Ho;Park, Young-Jin;Park, Youn-Sik
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.19 no.4
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    • pp.355-362
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    • 2009
  • Sound source localization method based on the time delay of arrival(TDOA) is applied to many research fields such as a robot auditory system, teleconferencing and so on. When multi-microphones are utilized to localize the source in 3 dimensional space, the conventional localization methods based on TDOA decide the actual source position using the TDOAs from all microphone arrays and the detection measure, which represents the errors between the actual source position and the estimated ones. Performance of these methods usually depends on the number of microphones because it determines the resolution of an estimated position. In this paper, we proposed the localization method using spatially mapped GCC functions. The proposed method does not use just TDOA for localization such as previous ones but it uses spatially mapped GCC functions which is the cross correlation function mapped by an appropriate mapping function over the spatial coordinate. A number of the spatially mapped GCC functions are summed to a single function over the global coordinate and then the actual source position is determined based on the summed GCC function. Performance of the proposed method for the noise effect and estimation resolution is verified with the real environmental experiment. The mean value of estimation error of the proposed method is much smaller than the one based on the conventional ones and the percentage of correct estimation is improved by 30% when the error bound is ${\pm}20^{\circ}$.

Factors for Speech Signal Time Delay Estimation (음성 신호를 이용한 시간지연 추정에 미치는 영향들에 관한 연구)

  • Kwon, Byoung-Ho;Park, Young-Jin;Park, Youn-Sik
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2008.04a
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    • pp.909-915
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    • 2008
  • Researches for time delay estimation had been studied broadly. However studies about factors for time delay estimation are insufficient, especially in case of real environment application. In 1997, Brandstein and Siverman announced that performance of time delay estimation deteriorates as reverberant time of room increases. Even though reverberant time of room is same, performance of estimation is different as the specific part of signals. In order to know that reason, we studied and analyzed the factors for time delay estimation using speech signal and room impulse response. In result, we can know that performance of time delay estimation is changed by different R/D ratio and signal characteristics in spite of same reverberant time.

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Spectral analysis of brain oscillatory activity (뇌파의 주파수축 분석법)

  • Min, Byoung-Kyong
    • Korean Journal of Cognitive Science
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    • v.20 no.2
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    • pp.155-181
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    • 2009
  • Psychophysiologists are often interested in the EEG signals that accompany certain psychological events. When one is interested in a time series of event-related changes in EEG, one focuses on examining how the waveforms recorded at individual electrode sites vary over time across one or more experimental conditions. This is an analysis of event-related potentials (ERPs). In addition to such a classical EEG analysis in the time domain, the EEG measures can be investigated in the frequency domain. Moreover, it has been demonstrated that spectral analyses can often yield significant insight into the functional cognitive correlations of the signals. Therefore, this review paper tries to summarize essential concepts (e.g. phase-locking) and conventional methods (e.g. wavelet transformation) for understanding spectral analyses of brain oscillatory activity. Phase-coherence is also introduced in relation to functional connectivity of the brain.

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