• Title/Summary/Keyword: Segregation of Signals

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Evaluation of a signal segregation by FDBM (FDBM의 음원분리 성능평가)

  • Lee, Chai-Bong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.12
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    • pp.1793-1802
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    • 2013
  • Various approaches for sound source segregation have been proposed. Among these approaches, frequency domain binaural model(FDBM) has the advantages of low computational load and effective howling cancellation. A binaural hearing assistance system based on FDBM has been proposed. This system can enhance desired signal based on the directivity information. Although FDBM has been evaluated in terms of signal-to-noise ratio (SNR) and coherence function, the evaluation results do not always agree with the human impressions. These evaluation methods provide physical measures, and do not take account of perceptual aspect of human being. Considering a binaural hearing assistance system as a one of major applications, the quality of segregated sound should keep level enough. In the paper, signal segregation performance by means of FDBM is evaluated by three objective methods, i.e., SNR, coherence and Perceptual Evaluation of Speech Quality(PESQ), to discuss the characteristic of FDBM on the sound source segregation performance. The simulation's evaluation results show that FDBM improves the quality of the left and right channel signals to an equivalent level. And the results suggest the possibility that PESQ provides a more useful measure than SNR and coherence in terms of the segregation performance of FDBM. The evaluation results by PESQ show the effects from segregation parameters and indicate appropriate parameters under the conditions. In the paper, signal segregation performance by means of FDBM is evaluated by three objective methods, i.e., SNR, coherence and PESQ, to discuss the characteristic of FDBM on the sound source segregation performance. The simulation's evaluation results show that FDBM improves the quality of the left and right channel signals to an equivalent level. And the results suggest the possibility that PESQ provides a more useful measure than SNR and coherence in terms of the segregation performance of FDBM. The evaluation results by PESQ show the effects from segregation parameters and indicate appropriate parameters under the conditions.

Distribution of the Slopes of Autocovariances of Speech Signals in Frequency Bands (음성 신호의 주파수 대역별 자기 공분산 기울기 분포)

  • Kim, Seonil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.5
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    • pp.1076-1082
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    • 2013
  • The frequency bands were discovered which maximize the slopes of autocovariances of speech signals in frequency domain to increase the possibility of segregation between speech signals and background noise signal. A speech signal is divided into blocks which include multiples of sampled data, then those blocks are transformed to frequency domain using Fast Fourier Transform(FFT). To find linear equation by Linear Regression, the coefficients of autocovariance within blocks of some frequency band are used. The slope of the linear equation which is called the slope of autocovariance is varied from band to band according to the characteristics of the speech signal. Using speech signals of a man which consist of 200 files, the coefficients of the slopes of autocovariances are analyzed and compared from band to band.

Classification of Speech and Car Noise Signals using the Slope of Autocovariances in Frequency Domain (주파수 영역 자기 공분산 기울기를 이용한 음성과 자동차 소음 신호의 구분)

  • Kim, Seon-Il
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.10
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    • pp.2093-2099
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    • 2011
  • Speech signal and car noise signal such as muffler noise are segregated from the one which has both signals mixed using statistical method. To classify speech signal from the other in segregated signals, FFT coefficients were obtained for all segments of a signal where each segment consists of 128 elements of a signal. For several coefficients of FFT corresponding to the low frequencies of a signal, autocovariances are calculated between coefficients of same order of all segments of a signal. Then they were averaged over autocovariances. Linear equation was eatablished for the those autocovariances using the linear regression method for each siganl. The coefficient of the slope of the line gives reference to compare and decide what the speech signal is. It is what this paper proposes. The results show it is very useful.

Towards Size of Scene in Auditory Scene Analysis: A Systematic Review

  • Kwak, Chanbeom;Han, Woojae
    • Korean Journal of Audiology
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    • v.24 no.1
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    • pp.1-9
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    • 2020
  • Auditory scene analysis is defined as a listener's ability to segregate a meaningful message from meaningless background noise in a listening environment. To gain better understanding of auditory perception in terms of message integration and segregation ability among concurrent signals, we aimed to systematically review the size of auditory scenes among individuals. A total of seven electronic databases were searched from 2000 to the present with related key terms. Using our inclusion criteria, 4,507 articles were classified according to four sequential steps-identification, screening, eligibility, included. Following study selection, the quality of four included articles was evaluated using the CAMARADES checklist. In general, studies concluded that the size of auditory scene increased as the number of sound sources increased; however, when the number of sources was five or higher, the listener's auditory scene analysis reached its maximum capability. Unfortunately, the score of study quality was not determined to be very high, and the number of articles used to calculate mean effect size and statistical significance was insufficient to draw significant conclusions. We suggest that study design and materials that consider realistic listening environments should be used in further studies to deep understand the nature of auditory scene analysis within various groups.

Towards Size of Scene in Auditory Scene Analysis: A Systematic Review

  • Kwak, Chanbeom;Han, Woojae
    • Journal of Audiology & Otology
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    • v.24 no.1
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    • pp.1-9
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    • 2020
  • Auditory scene analysis is defined as a listener's ability to segregate a meaningful message from meaningless background noise in a listening environment. To gain better understanding of auditory perception in terms of message integration and segregation ability among concurrent signals, we aimed to systematically review the size of auditory scenes among individuals. A total of seven electronic databases were searched from 2000 to the present with related key terms. Using our inclusion criteria, 4,507 articles were classified according to four sequential steps-identification, screening, eligibility, included. Following study selection, the quality of four included articles was evaluated using the CAMARADES checklist. In general, studies concluded that the size of auditory scene increased as the number of sound sources increased; however, when the number of sources was five or higher, the listener's auditory scene analysis reached its maximum capability. Unfortunately, the score of study quality was not determined to be very high, and the number of articles used to calculate mean effect size and statistical significance was insufficient to draw significant conclusions. We suggest that study design and materials that consider realistic listening environments should be used in further studies to deep understand the nature of auditory scene analysis within various groups.

Chromosome Aberrations in Porcine Embryo Produced by Nuclear Transfer with Somatic Cell

  • Ah, Ko-Seung;Jin, Song-Sang;Tae, Do-Jeong;Chung, Kil-Saeng;Lee, Hoon-Taek
    • Proceedings of the Korean Society of Embryo Transfer Conference
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    • 2002.11a
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    • pp.73-73
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    • 2002
  • Nuclear transfer (NT) techniques have advanced in the last years, and cloned animals have been produced by using somatic cells in several species including pig. However, it is difficult that the nuclear transfer porcine embryos development to blastocyst stage overcoming the cell block in vitro. Abnormal segregation of chromosomes in nuclear transferred embryos on genome activation stage bring about embryo degeneration, abnormal blastocyst, delayed and low embryo development. Thus, we are evaluated that the correlations of the frequency of embryo developmental rates and chromosome aberration in NT and In viかo fertilization (IVF) derived embryo. We are used for ear-skin-fibroblast cell in NT. If only karyotyping of embryonic cells are chromosomally abnormal, they may difficultly remain undetected. Then, we evaluate the chromosome aberrations, fluorescent in situ hybridization (FISH) with porcine chromosome 1 submetacentric specific DNA probe were excuted. In normal diploid cell nucleus, two hybridization signal was detected. In contrast, abnormal cell figured one or three over signals. The developmental rates of NT and IVF embryos were 55% vs 63%, 32% vs 33% and 13% vs 17% in 2 cell, 8 cell and blastocyst, respectively. When looking at the types of chromosome aberration, the detection of aneuploidy at Day 3 on the embryo culture. The percentage of chromosome aneuploidy of NT and IVF at 4-cell stage 40.0%, 31.3%, respectively. This result indicate that chromosomal abnormalities are associated with low developmental rate in porcine NT embryo. It is also suggest that abnormal porcine embryos produced by NT associated with lower implantation rate, increase abortion rate and production of abnormal fetuses.

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Speech Segmentation using Weighted Cross-correlation in CASA System (계산적 청각 장면 분석 시스템에서 가중치 상호상관계수를 이용한 음성 분리)

  • Kim, JungHo;Kang, ChulHo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.5
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    • pp.188-194
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    • 2014
  • The feature extraction mechanism of the CASA(Computational Auditory Scene Analysis) system uses time continuity and frequency channel similarity to compose a correlogram of auditory elements. In segmentation, we compose a binary mask by using cross-correlation function, mask 1(speech) has the same periodicity and synchronization. However, when there is delay between autocorrelation signals with the same periodicity, it is determined as a speech, which is considered to be a drawback. In this paper, we proposed an algorithm to improve discrimination of channel similarity using Weighted Cross-correlation in segmentation. We conducted experiments to evaluate the speech segregation performance of the CASA system in background noise(siren, machine, white, car, crowd) environments by changing SNR 5dB and 0dB. In this paper, we compared the proposed algorithm to the conventional algorithm. The performance of the proposed algorithm has been improved as following: improvement of 2.75dB at SNR 5dB and 4.84dB at SNR 0dB for background noise environment.