• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.683-687
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• 2010

This paper studied some methods which use frequency warping method that is the one of the speech transformation method to develope the robust speech recognition system for the emotional variation. For this purpose, the effect of emotional variations on the speech signal were studied using speech database containing various emotions and it is observed that speech spectrum is affected by the emotional variation and this effect is one of the reasons that makes the performance of the speech recognition system worse. In this paper, new training method that uses frequency warping in training process is presented to reduce the effect of emotional variation and the speech recognition system based on vocal tract length normalization method is developed to be compared with proposed system. Experimental results from the isolated word recognition using HMM showed that new training method reduced the error rate of the conventional recognition system using speech signal containing various emotions.

• The Journal of the Acoustical Society of Korea
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• v.29 no.5
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• pp.339-346
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• 2010

For the implementation of the crosstalk canceller, the filters with large length are needed, which is because that the length of the filters greatly depends on the length of the head-related impulse responses. In order to reduce the length of the crosstalk cancellation filters, many methods such as frequency warping, common acoustical pole and zero (CAPZ) modeling have been researched. In this paper, we propose a new method combining these two methods. To accomplish this, we design the filters using the CAPZ modeling on the warped domain, and then, we implement the filters using the poles and zeros de-warped to the linear domain. The proposed method provides improved channel separation performance through the frequency warping and significant reduction of the complexity through the CAPZ modeling. These are confirmed through various computer simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2407-2414
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• 1999

This paper introduces the concept of warped discrete cosine transform (WDCT) and an image compression algorithm based on the WDCT. The proposed WDCT is a cascade connection of a conventional DCT and all-pass filters whose parameters can be adjusted to provide frequency warping. In the proposed image compression scheme, the frequency response of the all-pass filter is controlled by a set of parameters with each parameter for a specified frequency range. For each image block, the best parameter is chosen from the set and is sent to the decoder as a side information along with the result of corresponding WDCT computation. For actual implementation, the combination of the all-pass IIR filters and the DCT can be viewed as a cascade of a warping matrix and the DCT matrix, or as a filter bank which is obtained by warping the frequency response of the DCT filter bank. Hence, the WDCT can be implemented by a single matrix computation like the DCT. The WDCT based compression, outperforms the DCT based compression, for high bit rate applications and for images with high frequency components.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.563-567
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• 2001

We generalize the widebane P0-weyl symbol (P0WS) and the widebane spreading function (WSF) using the generalized warping function . The new generalized P0WS and WSF are useful for analyzing system and communication channels producing generalized time shifts. We also investigated the relationship between the affine Wey1 symbol(AWS) and the P0WS. By using specific warping functions, we derive new P0WS and WSF as analysis tools for systems and communication channels with non-linear group delary characteristics. The new P0WS preserves specific types of changes imposed on random processes. The new WSF provides a new interpretation of output of system and communication channel as weighted superpositions of non-linear time shifts on the input. It is compared to the conventional method obtaining output of system and communication channel as a convention integration of the input with the impulse response of the system and the communication channel. The convolution integration can be interpreted as weighted superpositions of liner time shifts on the input where the weight is the impulse response of the system and the communication channel. Application examples in analysis and detection demonstrate the advantages of our new results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.2
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• pp.102-108
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.1
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• pp.95-102
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• 2007

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signals onto frequency domain. The raw signals can not show the significant feature, therefore difference values between the signal of the health conditions and that of the fault conditions are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the fault type. This study describes the results of detecting fault using wavelet analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.130-135
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• 2011

A study of the bending-extension-transverse shear coupled random response of the composite beams with thin-walled open sections subjected to various types of concentrated and distributed random excitations is dealt with in this paper. First of all, equations of motion of thin-walled composite H-type cross-section beams incorporating a number of nonclassical effects of transverse shear and primary and secondary warping, and anisotropy of constituent materials are derived. On the basis of derived equations of motion, analytical expressions for the displacement response of the composite beams are derived by using normal mode method combined with frequency response function method.

• Journal of KSNVE
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• v.9 no.6
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• pp.1193-1199
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• 1999

This paper deals with the free vibrations of circular curved beams with thin-walled cross-section. The differential equation for the coupled flexural-torsional vibrations of such beams with warping is solved numerically to obtain natural frequencies and mode shapes. The Runge-Kutta and determinant search methods, respectively, are used to solve the governing differential equation and to compute the eigenvalues. The lowest three natural frequencies and corresponding mode shapes are calculated for the thin-walled horizontally curved beams with hinged-hinged, hinged-clamped, and clamped-clamped end constraints. A wide range of opening angle of beam, warping parameter, and two different values of slenderness ratios are considered. Numerical results are compared with existing exact and numerical solutions by other methods.

• Phonetics and Speech Sciences
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• v.7 no.1
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• pp.3-10
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• 2015

In this paper, different frequency scales in cepstral feature extraction are evaluated for the text-independent speaker recognition. To this end, mel-frequency cepstral coefficients (MFCCs), linear frequency cepstral coefficients (LFCCs), and bilinear warped frequency cepstral coefficients (BWFCCs) are applied to the speaker recognition experiment. In addition, the spectro-temporal features extracted by the cepstral-time matrix (CTM) are examined as an alternative to the delta and delta-delta features. Experiments on the NIST speaker recognition evaluation (SRE) 2004 task are carried out using the Gaussian mixture model-universal background model (GMM-UBM) method and the joint factor analysis (JFA) method, both based on the ALIZE 3.0 toolkit. Experimental results using both the methods show that BWFCC with appropriate warping factor yields better performance than MFCC and LFCC. It is also shown that the feature set including the spectro-temporal information based on the CTM outperforms the conventional feature set including the delta and delta-delta features.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.290-291
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• 2008

The most popular speech feature used in speech recognition today is the Mel-Frequency Cepstral Coefficients (MFCC) algorithm, which could reflect the perception characteristics of the human ear more accurately than other parameters. This paper adopts MFCC and its first order difference, which could reflect the dynamic character of speech signal, as synthetical parametric representation. Furthermore, we quote Dynamic Time Warping (DTW) algorithm to search match paths in the pattern recognition process. We use the software "GoldWave" to record English digitals in the lab environments and the simulation results indicate the algorithm has higher recognition accuracy than others using LPCC, etc. as character parameters in the experiment for Digital Isolated Word Recognition (DIWR) system.