• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.3
• /
• pp.1-9
• /
• 1993

This paper discusses issues on the disign and implementation of real-time automatic speaker verification system, as well as the performance analysis of the implemented system. The system employs TI's TMS320C25 digital signal processor TMS320C25 and high speed SRAMs. The system is designed to be used stand-alone as well as via hand-shaking with IBM-PC. The speech parameters used for speaker verification are PARCOR and LPC-cepstrum coefficients, and the employed decision logics are those based on the generalized weighted distance comcept. The implemented system showed the performance of 5.3% error rate for the PARCOR coefficient, and 4.7% error rate for the LPG-cepstrum coefficient.

• The Journal of the Acoustical Society of Korea
• /
• v.15 no.5
• /
• pp.38-43
• /
• 1996

This paper compares the recognition performances of feature vectors known to be robust to the environmental noise. And, the speech subtraction technique is combined with the noise robust feature to get more performance enhancement. The experiments using SMC(Short time Modified Coherence) analysis, root cepstral analysis, LDA(Linear Discriminant Analysis), PLP(Perceptual Linear Prediction), RASTA(RelAtive SpecTrAl) processing are carried out. An isolated word recognition system is composed using semi-continuous HMM. Noisy environment experiments usign two types of noises:exhibition hall, computer room are carried out at 0, 10, 20dB SNRs. The experimental result shows that SMC and root based mel cepstrum(root_mel cepstrum) show 9.86% and 12.68% recognition enhancement at 10dB in compare to the LPCC(Linear Prediction Cepstral Coefficient). And when combined with spectral subtraction, mel cepstrum and root_mel cepstrum show 16.7% and 8.4% enhanced recognition rate of 94.91% and 94.28% at 10dB.

• Journal of Astronomy and Space Sciences
• /
• v.25 no.2
• /
• pp.71-76
• /
• 2008

Study of terrestrial impact craters is important not only in the field of the solar system formation and evolution but also of the Galactic astronomy. The terrestrial impact cratering record recently has been examined, providing short- and intermediate-term periodicities, such as, ${\sim}26$ Myrs, ${\sim}37$ Myrs. The existence of such a periodicity has an implication in the Galactic dynamics, since the terrestrial impact cratering is usually interpreted as a result of the environmental variation during solar orbiting in the Galactic plane. The aim of this paper is to search for a long-term periodicity with a novel method since no attempt has been made so far in searching a long-term periodicity in this research field in spite of its great importance. We apply the cepstrum analysis method to the terrestrial impact cratering record for the first time. As a result of the analysis we have found noticeable peaks in the Fourier power spectrum appear ing at periods of ${\sim}300$ Myrs and ${\sim}100$ Myrs, which seem in a simple resonance with the revolution period of the Sun around the Galactic center. Finally we briefly discuss its implications and suggest theoretical study be pursued to explain such a long-term periodicity.

• MALSORI
• /
• no.50
• /
• pp.111-122
• /
• 2004

Automatic detection of laryngeal diseases by voice is attractive because of its non-intrusive nature. Cepstrum based approach to detect laryngeal cancer shows reliable performance even when the periodicity of voice signals is severely lost, but it has a drawback that it is not robust to channel mismatch due to different microphone characteristics. In this paper, to deal with mismatched training and test microphone conditions, we investigate channel compensation techniques such as Cepstral Mean Subtraction (CMS) and Pole Filtered CMS (PFCMS). According to our experiments, PFCMS yields better performance than CMS. By using PFCMS, we obtained 12% and 40% error reduction over baseline and CMS, respectively.

• Proceedings of the IEEK Conference
• /
• 2000.09a
• /
• pp.153-156
• /
• 2000

본 논문에서는 음성 인식률 향상을 위한 여러 가지방법들 중에서 음성특징 파라미터 추출 방법에 관한 한가지 방법을 제시하였다. 본 논문에서는 청각 특성을 기반으로 한 MFCC(met frequency cepstrum coef-ficients)와 성능 향상을 위한 방법으로 GFCC (gamma-tone filter frequency cepstrum coefficients)를 제시하고 음성 인식을 수행하여 성능을 분석하였다. MFCC에서 일반적으로 사용하는 임계 대역 필터로 삼각 필터(triangular filter) 대신 청각 구조의 기저막(basilar membrane)특성을 묘사한 gammatone 대역 통과 필터를 이용하여 특징 파라미터를 추출하였다. DTW 알고리즘으로 인식률을 분석한 결과 삼각 대역 필터를 이용한 것보다 gammatone 대역 통과 필터를 이용한 추출법이 약 2∼3%의 성능 향상을 보였다.

• Proceedings of the Korea Contents Association Conference
• /
• 2004.11a
• /
• pp.308-313
• /
• 2004

In this paper, we compared and analyzed the discrimination performance of speech/music about combinations of each features parameter. Audio signals are classified into 3 classes (speech, music, speech and music). On three types of features, Mel-cepstrum, energy, zero-crossings used to the experiments. Then compared and analyzed the best of the combinations between features to speech/ music discrimination performance. The best result is achieved using Mel-cepstrum, energy and zero-crossings in a single feature vector (speech: 95.1%, music: 61.9%, speech & music: 55.5%).

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.123-127
• /
• 1997

Recently, it is gradually raised necessity that interface is measured accurately and managed in industrial circles and medical world, An Ultrasonic wave transmitted from a focused beam transducer is being expected as a powerful tool for NDE of micro-defect. The ultrasonic NDE of the defect is based on the form of the wave reflected form the interface In this study, regarding to the thickness of film which is in opaque object and thickness measurement was done by MEM-cepstrum analysis of received ultrasonic wave. In measument results, film thickness which is beyond distance resolution capacity was measured accurately. Also, automatically repeated discrimination analysis method can be decided in the category of all kinds of defects on semiconductor package.

• The Journal of the Acoustical Society of Korea
• /
• v.11 no.4
• /
• pp.14-21
• /
• 1992

The waveform coding is concerned with simply preserving the wave shape of speech signal through a redundancy reduction process. In area of the speech synthesis, the waveform codings with high quality are mainly used to the synthesis by analysis. However, because the parameters of this coding are not classified as either excitation parameters and vocal tract parameters, it is difficult to applying the waveform coding to the synthesis by rule. In this paper, we proposed a new pitch alternation method that can change the pitch periods in the waveform coding by using the cepstrum analysis. Thus, it is possible that the waveform coding is carried out the synthesis by rule in speech processing.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2001.06a
• /
• pp.285-288
• /
• 2001

In this paper, we proposed new method of speech feature extraction using ICA(Independent Component Analysis) which minimized the dependency and correlation among speech signals on purpose to separate each component in the speech signal. ICA removes the repeating of data after finding the axis direction which has the greatest variance in input dimension. We verified improvement of speech recognition ability with training and recognition experiments when ICA compared with conventional mel-cepstrum features using HMM. Also, we can see that ICA dealt with the situation of recognition ability decline that is caused by environmental noise.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.12a
• /
• pp.181-184
• /
• 2000

The new method of feature extraction is proposed, considering the statistic feature of human voice, unlike the conventional methods of voice extraction. PCA(principal Component Analysis) is applied to this new method. PCA removes the repeating of data after finding the axis direction which has the greatest variance in input dimension. Then the new method is applied to real voice recognition to assess performance. When results of the number recognition in this paper and the conventional Mel-Cepstrum of voice feature parameter are compared, there is 0.5% difference of recognition rate. Better recognition rate is expected than word or sentence recognition in that less convergence time than the conventional method in extracting voice feature. Also, better recognition tate is expected when the optimum vector is used by statistic feature of data.