• Speech Sciences
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• v.10 no.2
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• pp.57-64
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• 2003

The cepstrum coefficients are the most popular feature for speech recognition or speaker recognition. The cepstrum coefficients are also used for speech synthesis and speech coding but has major drawback of long processing time. In this paper, we proposed a new method that can reduce the processing time of FFT cepstrum analysis. We use the normal ordered inputs for FFT function and the bit-reversed inputs for IFFT function. Therefore we can omit the bit-reversing process and reduce the processing time of FFT ceptrum analysis.

• Journal of Biomedical Engineering Research
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• v.15 no.2
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• pp.159-166
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• 1994

A new pattern classification algorithm using cepstrum to analyze lung sounds for the classification of pattern with pulmonary and bronchial disorders is proposed. To evaluate the perfomance of the proposed method, the results are compared to the pattern classification with the AR modeling method. In the experiment lung sounds recorded for the training of physician used. As a results, the accuracy of the cepstrum classification is 92.3 % and AR modeling is the 53.8 %, therefore cepstrum modeling method has very high performance than AR and it turned out to be a very efficient algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2521-2526
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• 2011

This paper proposes a speaker recognition algorithm using a perceptron neural network and LPC (Linear Predictive Coding) cepstrum coefficients. The proposed algorithm first detects the voiced sections at each frame. Then, the LPC cepstrum coefficients which have speaker characteristics are obtained by the linear predictive analysis for the detected voiced sections. To classify the obtained LPC cepstrum coefficients, a neural network is trained using the LPC cepstrum coefficients. In this experiment, the performance of the proposed algorithm was evaluated using the speech recognition rates based on the LPC cepstrum coefficients and the neural network.

• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.28-33
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• 2016

Since defects in the wheels of railway vehicles, which occur due to wears with the rail, cause serious damage to the running device, the diagnostic monitoring system for condition-based maintenance is required to secure the driving safety. In this paper, we studied to apply a useful Cepstrum analysis to detect periodic structure in spectrum among the vibration signal processing techniques for the fault diagnosis of a rotating body such as wheel. In order to analyze in variations of train velocity, the Cepstrum analysis was performed after a domain change of the vibration signal from time domain to rotation angle domain. When domains change, it is important to use a interpolation for a uniform interval of the rotation angle. Finally, the Cepstrum analysis for wheel flat detection was verified by using the vibration signal including the disturbance resulting from the rail irregularities and the vibration of bogie components.

• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.225-227
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• 1995

This paper compared waveform, cepstrum, and spline wavelet features with nonlinear discriminant analysis. This measure shows efficiency of speech parametrization better than old linear separability criteria and can be used to measure the efficiency of each layer of certain system. Spline wavelet transform has larger gap among classes and cepstrum is clustered better than the spline wavelet feature. Both features do not have good property for classification and we will compare Gabor wavelet transform, Mel cepstrum, delta cepstrum, etc.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.61-74
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• 2004

In this paper, a contort- and speaker-dependent cepstrum extraction method and a channel normalization method for minimizing the loss of speaker characteristics in the cepstrum were proposed for a robust speaker recognition system over the channel. The proposed extraction method creates a cepstrum based on the pitch synchronous analysis using the inherent pitch of the speaker. Therefore, the cepstrum called the 〃pitch synchronous cepstrum〃 (PSC) represents the impulse response of the vocal tract more accurately in voiced speech. And the PSC can compensate for channel distortion because the pitch is more robust in a channel environment than the spectrum of speech. And the proposed channel normalization method, the 〃formant-broadened pitch synchronous CMS〃 (FBPSCMS), applies the Formant-Broadened CMS to the PSC and improves the accuracy of the intraframe processing. We compared the text-independent closed-set speaker identification on 56 females and 112 males using TIMIT and NTIMIT database, respectively. The results show that pitch synchronous km improves the error reduction rate by up to 7.7% in comparison with conventional short-time cepstrum and the error rates of the FBPSCMS are more stable and lower than those of pole-filtered CMS.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.721-726
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• 2008

Community Noise has been great concerned in public. A road traffic noise has affected too much damage on quiet living environment. In this paper, About measured from the measure point noise and the noise signal processing techniques applied to the occurrence of the noise source with a path to reach this measure point to the measured data to determine signal processor for Complex Cepstrum Analysis of how to apply for research.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.5 s.170
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• pp.72-79
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• 2005

Gearing system emits inconsistent noise from gear teeth impact in case of gear defects. But, it is not easy for inspection operator in production line to distinguish objectively the defective product. Therefore, customer complains continuously bad noise of the geared motor. Because impulsive signal at low frequency has a tendency not to appear in frequency domain, it is difficult to separate the gear inconsistent noise of defective gear from overall geared motor's noise using general signal processing method such as FFT. In this paper, the method to estimate more objectively the inconsistent noise of gearing system and to measure the quantities is suggested. Suggested method uses Cepstrum, Autocorrelation, Comb Lifter and Inverse Cepstrum by turns to make objective quantities about noise level.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.33 no.2
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• pp.64-76
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• 2022

Praat is a useful analysis tool for linguists, engineers, doctors, speech-language pathologits, music majors, and natural scientists. Basic parameters including duration, pitch, energy and perturbation parameters such as jitter and shimmer can be easily measured and manipulated in the sound editor. When a more in-depth analysis is needed, it is recommended to understand the advanced menus of the object window and learn how to use them. Among the object window menus, vowel formant analysis, spectrum analysis, and cepstrum analysis can be cited as useful ones in the clinical field. The spectrum object can be usefully used for voice quality measurement and diagnosis of patients with voice disorders by showing the energy distribution according to frequency axis (domain). A cepstrum object is useful for speech analysis when periodicity of the sound object is not measurable. The low to high ratio obtained from the spectral object and the CPPs measured from the cepstrum object have attracted many researchers, and it has been proven that the CPPs measured in Praat are relatively excellent.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.5
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• pp.447-453
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• 2009

Community noise has been great concerned in public. A traffic noise from a road or a railway has affected too mush damage on quiet living environment. In this paper, a measured noise signal on a street has been applied to extract a noise source and a path by using a complex cepstrum. An example shows that the waveform of the source and the path could be separated if a temporal windowing is properly applied.