• Title/Summary/Keyword: 오디오 신호의 정현파 모델링

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Sinusoidal Modeling of Polyphonic Audio Signals Using Dynamic Segmentation Method (동적 세그멘테이션을 이용한 폴리포닉 오디오 신호의 정현파 모델링)

  • 장호근;박주성
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.4
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    • pp.58-68
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    • 2000
  • This paper proposes a sinusoidal modeling of polyphonic audio signals. Sinusoidal modeling which has been applied well to speech and monophonic signals cannot be applied directly to polyphonic signals because a window size for sinusoidal analysis cannot be determined over the entire signal. In addition, for high quality synthesized signal transient parts like attacks should be preserved which determines timbre of musical instrument. In this paper, a multiresolution filter bank is designed which splits the input signal into six octave-spaced subbands without aliasing and sinusoidal modeling is applied to each subband signal. To alleviate smearing of transients in sinusoidal modeling a dynamic segmentation method is applied to subbands which determines the analysis-synthesis frame size adaptively to fit time-frequency characteristics of the subband signal. The improved dynamic segmentation is proposed which shows better performance about transients and reduced computation. For various polyphonic audio signals the result of simulation shows the suggested sinusoidal modeling can model polyphonic audio signals without loss of perceptual quality.

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Sinusoidal Modeling of Audio Signals Using Perceptually Weighted Matching Pursuit (지각적으로 가중된 매칭 퍼슈잇을 이용한 오디오 신호의 정현파 모델링)

  • 김연지;이인성
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.2
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    • pp.96-103
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    • 2003
  • This paper describes a method for sinusoidal modeling of audio signals using perceptually weighted matching pursuit. Matching pursuits extracts iteratively the greatest energy signals from the input signals until the residual between the original and the reconstructed signal is zero. In this paper, perceptual matching pursuits using psychoacoustic model to matching pursuit extracts greatest perceived energy iteratively. To evaluate the performance of the perceptual matching pursuits it is compared with the sinusoidal matching pursuits which is not included perceptual weighting. For various audio signals the result of simulation shows that the perceptual matching pursuit is superior to the sinusoidal matching pursuits, especially for a high change rate in time domain it can synthesized original signal.

Time-Scale Modification of Polyphonic Audio Signals Using Sinusoidal Modeling (정현파 모델링을 이용한 폴리포닉 오디오 신호의 시간축 변화)

  • 장호근;박주성
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.2
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    • pp.77-85
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    • 2001
  • This paper proposes a method of time-scale modification of polyphonic audio signals based on a sinusoidal model. The signals are modeled with sinusoidal component and noise component. A multiresolution filter bank is designed which splits the input signal into six octave-spaced subbands without aliasing and sinusoidal modeling is applied to each subband signal. To alleviate smearing of transients in time-scale modification a dynamic segmentation method is applied to subbands which determines the analysis-synthesis frame size adaptively to fit time-frequency characteristics of the subband signal. For extracting sinusoidal components and calculating their parameters matching pursuit algorithm is applied to each analysis frame of subband signal. In accordance with spectrum analysis a psychoacoustic model implementing the effect of frequency masking is incorporated with matching pursuit to provide a resonable stop condition of iteration and reduce the number of sinusoids. The noise component obtained by subtracting the synthesized signal with sinusoidal components from the original signal is modeled by line-segment model of short time spectrum envelope. For various polyphonic audio signals the result of simulation shows suggested sinusoidal modeling can synthesize original signal without loss of perceptual quality and do more robust and high quality time-scale modification for large scale factor because of representing transients without any perceptual loss.

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