• Title/Summary/Keyword: 백색잡음

Search Result 378, Processing Time 0.029 seconds

배경잡음 하에서의 신경회로망에 의한 남성화자 및 여성화자의 성별인식 알고리즘

  • Choe, Jae-Seung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2013.05a
    • /
    • pp.515-517
    • /
    • 2013
  • 본 논문에서는 잡음 환경 하에서 남녀 성별인식이 가능한 신경회로망에 의한 화자종속 음성인식 알고리즘을 제안한다. 본 논문에서 제안한 음성인식 알고리즘은 남성화자 및 여성화자를 인식하기 위하여 LPC 켑스트럼 계수를 사용하여 신경회로망에 의하여 학습된다. 본 실험에서는 백색잡음 및 자동차잡음에 대하여 신경회로망의 네크워크에 대한 인식결과를 나타낸다. 인식실험의 결과로부터 백색잡음에 대해서는 최대 96% 이상의 인식률, 자동차잡음에 대해서는 최대 88% 이상의 인식률을 구하였다.

  • PDF

Noise Reduction Algorithm in Speech by Wiener Filter (위너필터에 의한 음성 중의 잡음제거 알고리즘)

  • Choi, Jae-Seung
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.8 no.9
    • /
    • pp.1293-1298
    • /
    • 2013
  • This paper proposes a noise reduction algorithm using Wiener filter to remove the noise components from the noisy speech in order to improve the speech signal. The proposed algorithm first removes the noise spectrums of white noise from the noisy signal based on the noise reshaping and reduction method at each frame. And this algorithm enhances the speech signal using Wiener filter based on linear predictive coding analysis. In this experiment, experimental results of the proposed algorithm demonstrate using the speech and noise data by Japanese male speaker. Based on measuring the spectral distortion (SD) measure, experiments confirm that the proposed algorithm is effective for the speech by contaminated white noise. From the experiments, the maximum improvement in the output SD values was 4.94 dB better for white noise compared with former Wiener filter.

Subspace Speech Enhancement Using Subband Whitening Filter (서브밴드 백색화 필터를 이용한 부공간 잡음 제거)

  • 김종욱;유창동
    • The Journal of the Acoustical Society of Korea
    • /
    • v.22 no.3
    • /
    • pp.169-174
    • /
    • 2003
  • A novel subspace speech enhancement using subband whitening filter is proposed. Previous subspace speech enhancement method either assumes additive white noise or uses whitening filter as a pre-processing for colored noise. The proposed method tries to minimize the signal distortion while reducing residual noise by processing the signal using subband whitening filter. By incorporating the notion of subband whitening filter, spectral resolution in Karhunen-Loeve(KL) domain is improved with the negligible additional computational load. The proposed method outperforms both the subspace method suggested by Ephraim and the spectral subtraction suggested by Boll in terms of segmental signal-to-noise ratio (SNRseg) and perceptual evaluation of speech quality (PESQ).

An Effect of the Prefrontal Lobe Influenced by Game Music Mixed with White Noise (백색잡음을 혼합한 게임음악이 전전두엽에 미치는 영향)

  • Choi, Jong-Yun;Rhee, Dae-Woong
    • Journal of Korea Game Society
    • /
    • v.11 no.6
    • /
    • pp.3-11
    • /
    • 2011
  • The sound of digital media would be able to perform communication by stimulating body's senses. Because the sound stimuli could arouse a person into the physiological excitement and sensitivity, which appear as the changes of heartbeat, blood pressure, brain waves(EEG) signals. In this paper, we would like to examine whether the game music mixed with relaxing white noises has an effect to relax game player or not through the EEG changes of game players. For the experiment, we divided game players into group A that plays game while hearing game music mixed with white noises, and group B that plays game while hearing game music not mixed. And we measured the EEG changes of the prefrontal lobe between two groups. The result shows that the game music mixed with white noises has an relaxing effect for the left brain, but fall short of the expectations for the right brain. It would be a basic research which will contribute to the development of serious games for psychotherapy using relaxing white noises.

Speaker-dependent Speech Recognition Algorithm for Male and Female Classification (남녀성별 분류를 위한 화자종속 음성인식 알고리즘)

  • Choi, Jae-Seung
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.17 no.4
    • /
    • pp.775-780
    • /
    • 2013
  • This paper proposes a speaker-dependent speech recognition algorithm which can classify the gender for male and female speakers in white noise and car noise, using a neural network. The proposed speech recognition algorithm is trained by the neural network to recognize the gender for male and female speakers, using LPC (Linear Predictive Coding) cepstrum coefficients. In the experiment results, the maximal improvement of total speech recognition rate is 96% for white noise and 88% for car noise, respectively, after trained a total of six neural networks. Finally, the proposed speech recognition algorithm is compared with the results of a conventional speech recognition algorithm in the background noisy environment.

Analysis of De-noising by Thresholding (문턱치에 따른 잡음제거 분석)

  • Seo, Jung-Ick;Park, Eun-kyoo
    • Journal of the Korea society of information convergence
    • /
    • v.6 no.2
    • /
    • pp.45-49
    • /
    • 2013
  • Electrocardiogram(ECG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of cadiac disease diagnosis with removing signal white-noise. Sampling signal was made with generating white-noise. The noise were removed using wavelet transforms and thresholding. Removed noise were compared numerical using SNR(signal to noise ratio). The results compared SNR showed that SURE method was 5.931, 4.9301 in 3, 5dB noise, uninversal was 3.6590, 1.9698 in 7, 9dB noise. De-noising by Thresholding removed noise effectively. ECG signal is expected to improve the accuracy of cadiac desease dianosis.

  • PDF

Noisy Speech Enhancement by Restoration of DFT Components Using Neural Network (신경회로망을 이용한 DFT 성분 복원에 의한 음성강조)

  • Choi, Jae-Seung
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.14 no.5
    • /
    • pp.1078-1084
    • /
    • 2010
  • This paper presents a speech enhancement system which restores the amplitude components and phase components by discrete Fourier transform (DFT), using neural network training by back-propagation algorithm. First, a neural network is trained using DFT amplitude components and phase components of noisy speech signal, then the proposed system enhances speech signals that are degraded by white noise using a neural network. Experimental results demonstrate that speech signals degraded by white noise are enhanced by the proposed system using the neural network, whose inputs are DFT amplitude components and phase components. Based on measuring spectral distortion measurement, experiments confirm that the proposed system is effective for white noise.

A study of Brown Noise Weight in Optimization of Depression (우울증에 최적화된 갈색잡음 가중치에 관한 연구)

  • Park, Hyung-Woo;Jee, Sang-Hwi;Bae, Myung-Jin
    • Proceedings of the Korean Society of Computer Information Conference
    • /
    • 2016.01a
    • /
    • pp.21-22
    • /
    • 2016
  • 우울증은 감정을 조절하는 뇌의 기능의 변화가 생겨 부정적인 감정이 나타나는 병이다. 불안장애와 우울증은일반인구중 15%가 평생 동안 한번 이상 앓는 질환이다. 우울증환자는 일반인보다 불안한감정의 원인인 델타파가 많거나 좌측 전두엽의 알파파가 증가하고, 우측 전두엽은 베타파가 증가하는 특징을 가지고 있다. 선행연구에서는 백색잡음을 우울증환자의 증상완화에 사용하였다. 우울증 환자에게는 백색잡음보다는 유색(갈색)잡음이 치료에 더 효과적인 연구를 기반으로 하여 무음 상태, 갈색잡음, 고주파 가중치를 적용한 갈색잡음, 청감특성을 고려한 가중치를 적용한 갈색잡음을 들었을 때 의 뇌파에 대하여 살펴보았다. 그 중 갈색잡음과 청감특성을 고려한 가중치를 적용한 갈색잡음의 경우가 가장효과가 좋았다.

  • PDF

Improvement of Signal-to-Noise Ratio for Speech under Noisy Environment (잡음환경 하에서의 음성의 SNR 개선)

  • Choi, Jae-Seung
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.17 no.7
    • /
    • pp.1571-1576
    • /
    • 2013
  • This paper proposes an improvement algorithm of signal-to-noise ratios (SNRs) for speech signals under noisy environments. The proposed algorithm first estimates the SNRs in a low SNR, mid SNR and high SNR areas, in order to improve the SNRs in the speech signal from background noise, such as white noise and car noise. Thereafter, this algorithm subtracts the noise signal from the noisy speech signal at each bands using a spectrum sharpening method. In the experiment, good signal-to-noise ratios (SNR) are obtained for white noise and car noise compared with a conventional spectral subtraction method. From the experiment results, the maximal improvement in the output SNR results was approximately 4.2 dB and 3.7 dB better for white noise and car noise compared with the results of the spectral subtraction method, in the background noisy environment, respectively.

Spectrum Based Detector in Non-white Noise Environment (비백색 잡음 환경에 적합한 스펙트럼 기반 탐지기)

  • Yu, Seog-Kun;Joo, Eon-Kyeong
    • Journal of the Institute of Electronics Engineers of Korea TC
    • /
    • v.46 no.10
    • /
    • pp.8-13
    • /
    • 2009
  • The MF(matched filter) is the optimum signal detector that maximizes the output instantaneous signal power to average noise power ratio in white noise environment. But it cannot give the optimum detection performance if the background noise is not white. So, the whitening process preceding the matched filter is needed in the conventional detector which results in a PWMF(pre-whitening matched filter). Its performance is mainly affected by the estimation accuracy of non-white noise model which is used in the whitening procedure. To estimate more accurate model to improve performance, the computational complexity is increased. Therefore, a spectrum based detector which shows better performance than the PWMF under the similar complexity condition or less complexity under the similar performance condition is proposed in this paper. And its performance and complexity are analyzed and compared with the conventional PWMF.