• 제목/요약/키워드: Spectral Information Entropy

검색결과 24건 처리시간 0.031초

FFT와 MFB Spectral Entropy를 이용한 GMM 기반의 감정인식 (Speech Emotion Recognition Based on GMM Using FFT and MFB Spectral Entropy)

  • 이우석;노용완;홍광석
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 심포지엄 논문집 정보 및 제어부문
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    • pp.99-100
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    • 2008
  • This paper proposes a Gaussian Mixture Model (GMM) - based speech emotion recognition methods using four feature parameters; 1) Fast Fourier Transform(FFT) spectral entropy, 2) delta FFT spectral entropy, 3) Mel-frequency Filter Bank (MFB) spectral entropy, and 4) delta MFB spectral entropy. In addition, we use four emotions in a speech database including anger, sadness, happiness, and neutrality. We perform speech emotion recognition experiments using each pre-defined emotion and gender. The experimental results show that the proposed emotion recognition using FFT spectral-based entropy and MFB spectral-based entropy performs better than existing emotion recognition based on GMM using energy, Zero Crossing Rate (ZCR), Linear Prediction Coefficient (LPC), and pitch parameters. In experimental Results, we attained a maximum recognition rate of 75.1% when we used MFB spectral entropy and delta MFB spectral entropy.

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Vocal Effort Detection Based on Spectral Information Entropy Feature and Model Fusion

  • Chao, Hao;Lu, Bao-Yun;Liu, Yong-Li;Zhi, Hui-Lai
    • Journal of Information Processing Systems
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    • 제14권1호
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    • pp.218-227
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    • 2018
  • Vocal effort detection is important for both robust speech recognition and speaker recognition. In this paper, the spectral information entropy feature which contains more salient information regarding the vocal effort level is firstly proposed. Then, the model fusion method based on complementary model is presented to recognize vocal effort level. Experiments are conducted on isolated words test set, and the results show the spectral information entropy has the best performance among the three kinds of features. Meanwhile, the recognition accuracy of all vocal effort levels reaches 81.6%. Thus, potential of the proposed method is demonstrated.

가변위치 고음성인식 기술을 이용한 무선 홈 네트워크 시스템 구현에 관한 연구 (A Study on the Realization of Wireless Home Network System Using High-performance Speech Recognition in Variable Position)

  • 윤준철;최상방;박찬섭;김세영;김기만;강석엽
    • 한국정보통신학회논문지
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    • 제14권4호
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    • pp.991-998
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    • 2010
  • 실내 환경에서 음성인식 기술을 이용한 무선 홈 네트워크 시스템 구현에 있어, 잡음과 실내 잔향음은 시스템 성능 저하의 주요 원인이다. 본 연구에서는 실내 인식환경에서 스펙트럼 엔트로피(Spectral entropy) 기반의 음성 구간검출법을 이용하여 잔향음(reverberation) 및 실내잡음에 강인한 음성인식 홈 네트워크 시스템을 구현하고자 한다. 스펙트럼 차감법(Spectral Subtraction)은 잔향으로 인해 왜곡된 신호를 스펙트럼 상에서 제거하여 잔향의 효과를 줄일 수 있고 음성신호와 독립적인 잡음을 제거 할 수 있다. 효과적인 스펙트럼 차감을 위해서는 음성과 비음성 구간의 정확한 구분이 수반되어야 하며 이를 위해서 엔트로피 기반의 음성 구간 검출법을 적용하여 성능을 향상시킨다. 모의 및 실내환경 실험 결과 Spectral entropy 기반의 음성 구간 검출법을 이용할 경우 실내 잔향 및 잡음환경에서 명령어 인식률의 향상이 증명되었다.

Robust Entropy Based Voice Activity Detection Using Parameter Reconstruction in Noisy Environment

  • Han, Hag-Yong;Lee, Kwang-Seok;Koh, Si-Young;Hur, Kang-In
    • Journal of information and communication convergence engineering
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    • 제1권4호
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    • pp.205-208
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    • 2003
  • Voice activity detection is a important problem in the speech recognition and speech communication. This paper introduces new feature parameter which are reconstructed by spectral entropy of information theory for robust voice activity detection in the noise environment, then analyzes and compares it with energy method of voice activity detection and performance. In experiments, we confirmed that spectral entropy and its reconstructed parameter are superior than the energy method for robust voice activity detection in the various noise environment.

음성 활동 구간 검출을 위한 스펙트랄 엔트로피의 재구성 효과 (Reconstruction Effect of the Spectral Entropy for the Voice Activity Detection)

  • 권호민;한학용;이광석;고시영;허강인
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 2002년도 하계학술발표대회 논문집 제21권 1호
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    • pp.25-28
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    • 2002
  • Voice activity detection is important Problem in the speech recognition and communication. This paper introduces feature parameter which is reconstructed by the spectral entropy of information theory for the robust voice activity detection in the noise environment, analyzes and compares it with the energy method of voice activity detection and performance. In experiment, we confirmed that the spectral entropy is more feature parameter than the energy method for the robust voice activity detection in the various noise environment.

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잔향제거를 이용한 음성통신 시스템 성능 향상 (Performance Enhancement of Speech Communication System using Reverberation Rejection)

  • 김세영;강석엽;김기만
    • 한국정보통신학회논문지
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    • 제13권10호
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    • pp.2211-2217
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    • 2009
  • 본 논문에서는 잔향이 존재하는 환경에서 단일 마이크로폰을 사용한 음성 개선 방법을 제시한다. 스펙트럼 차감법(Spectral Subtraction)은 스펙트럼 상에서 잔향성분 및 잡음을 제거 할 수 있는 효과적인 방법이다. 스펙트럼 차감법은 음성과 비음성 구간의 정확한 구분을 필요로 하며 성능을 향상시키기 위해 본 논문에서는 엔트로피(Entropy) 기반의 음성 구간 검출법을 적용하였다. 제시된 방법을 기존의 에너지 검출 기반의 음성 검출법을 적용한 스펙트럼 차감법과 비교하여 성능 평가를 수행하였다. SNR 및 잔향시간에 따른 잔향 제거비율을 평가지표로 사용하였으며, 시뮬레이션 결과 기존의 스펙트럼 차감법과 비교하여 제시된 방법이 우수한 성능을 보였다.

엔트로피와 하모닉 검출을 이용한 잡음환경에 강인한 음성검출 (Robust Voice Activity Detection in Noisy Environment Using Entropy and Harmonics Detection)

  • 최갑근;김순협
    • 대한전자공학회논문지SP
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    • 제47권1호
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    • pp.169-174
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    • 2010
  • 이 논문은 잡음환경에서 음성인식률 향상을 위한 끝점 검출 방법에 대해 소개한다. 제안된 방법은 엔트로피와 음성의 하모닉 검출을 이용해 음성 구간과 비음성 구간을 검출한다. 음성의 스펙트럴 에너지에 대한 엔트로피를 사용하여 끝점검출을 하게 되면 비교적 높은 SNR 환경(SNR 15dB)에서는 성능이 우수하나 잡음환경의 변화에 따라 음성과 비음성의 문턱값이 변화 하여 낮은 SNR환경(SNR 0dB)에서는 정확한 끝점 검출이 어렵다. 본 논문은 낮은 SNR 환경(0dB)에서도 정확한 끝점을 검출할 수 있도록 음성의 스펙트럴 엔트로피와 하모닉 성분을 검출하여 끝점을 검출하는 방법을 제안한다. 실험결과 기존의 엔트로피만을 이용한 방법보다 개선된 성능을 보였다.

Hyperbolic Reaction-Diffusion Equation for a Reversible Brusselator: Solution by a Spectral Method

  • 이일희;김광연;조웅인
    • Bulletin of the Korean Chemical Society
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    • 제20권1호
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    • pp.35-41
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    • 1999
  • Stability characteristics of hyperbolic reaction-diffusion equations with a reversible Brusselator model are investigated as an extension of the previous work. Intensive stability analysis is performed for three important parameters, Nrd, β and Dx, where Nrd is the reaction-diffusion number which is a measure of hyperbolicity, β is a measure of reversibility of autocatalytic reaction and Dx is a diffusion coefficient of intermediate X. Especially, the dependence on Nrd of stability exhibits some interesting features, such as hyperbolicity in the small Nrd region and parabolicity in the large Nrd region. The hyperbolic reaction-diffusion equations are solved numerically by a spectral method which is modified and adjusted to hyperbolic partial differential equations. The numerical method gives good accuracy and efficiency even in a stiff region in the case of small Nrd, and it can be extended to a two-dimensional system. Four types of solution, spatially homogeneous, spatially oscillatory, spatio-temporally oscillatory and chaotic can be obtained. Entropy productions for reaction are also calculated to get some crucial information related to the bifurcation of the system. At the bifurcation point, entropy production changes discontinuously and it shows that different structures of the system have different modes in the dissipative process required to maintain the structure of the system. But it appears that magnitude of entropy production in each structure give no important information related for states of system itself.

SPATIO-SPECTRAL MAXIMUM ENTROPY METHOD: II. SOLAR MICROWAVE IMAGING SPECTROSCOPY

  • Bong, Su-Chan;Lee, Jeong-Woo;Gary Dale E.;Yun Hong-Sik;Chae Jong-Chul
    • 천문학회지
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    • 제38권4호
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    • pp.445-462
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    • 2005
  • In a companion paper, we have presented so-called Spatio-Spectral Maximum Entropy Method (SSMEM) particularly designed for Fourier-Transform imaging over a wide spectral range. The SSMEM allows simultaneous acquisition of both spectral and spatial information and we consider it most suitable for imaging spectroscopy of solar microwave emission. In this paper, we run the SSMEM for a realistic model of solar microwave radiation and a model array resembling the Owens Valley Solar Array in order to identify and resolve possible issues in the application of the SSMEM to solar microwave imaging spectroscopy. We mainly concern ourselves with issues as to how the frequency dependent noise in the data and frequency-dependent variations of source size and background flux will affect the result of imaging spectroscopy under the SSMEM. We also test the capability of the SSMEM against other conventional techniques, CLEAN and MEM.

$2^{nd}$ order maximum entropy method를 이용한 근피로도의 측정에 관한 연구 (A study on monitoring of fatigue using the $2^{nd}$ order maximum entropy method)

  • 조승진;김민수;이금원;김경기;김선일;박홍식;이강목
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1990년도 춘계학술대회
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    • pp.47-50
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    • 1990
  • In this study, the degree of spectral transfer to lower frequency caused by accumulation of Latic acid inside the muscle is estimated the convintional dip analysis, zero-crossing method and FFT method have intrinsic errors and estimation problems in case of severe noise. The new spectral analysis method using "$2^{nd}$ order Maximum Entropy Method" was applied to estimate mean frequency and we confirmed that this new method yields fast and reliable estimation over the FFT method.

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