• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.47-75
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• 2011

An accurate substructural synthesis method including random responses synthesis, frequency-response functions synthesis and mid-order modes synthesis is developed based on rigorous substructure description, dynamic condensation and coupling. An entire structure can firstly be divided into several substructures according to different functions, geometric and dynamic characteristics. Substructural displacements are expressed exactly by retained mid-order fixed-interfacial normal modes and residual constraint modes. Substructural interfacial degree-of-freedoms are eliminated by interfacial displacements compatibility and forces equilibrium between adjacent substructures. Then substructural mode vibration equations are coupled to form an exact-condensed synthesized structure equation, from which structural mid-order modes are calculated accurately. Furthermore, substructural frequency-response function equations are coupled to yield an exact-condensed synthesized structure vibration equation in frequency domain, from which the generalized structural frequency-response functions are obtained. Substructural frequency-response functions are calculated separately by using the generalized frequency-response functions, which can be assembled into an entire-structural frequency-response function matrix. Substructural power spectral density functions are expressed by the exact-synthesized substructural frequency-response functions, and substructural random responses such as correlation functions and mean-square responses can be calculated separately. The accuracy and capacity of the proposed substructure synthesis method is verified by numerical examples.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1127-1130
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• 1999

In this paper, using one method of Additive Synthesis, Analysis-by-synthesis/Overlap-Add (ABS/OLA) method, analysis and synthesis of musical tones is processed. But peak detection of frequency domain is processed by proposed method considering the view of acoustics. It is that that harmonics frequency is times of main frequency. Using this fact, peak detection of frequency domain is useful for detection of tonal component identified musical note. It is possible to realize high-quality lour bit rate audio.

• Phonetics and Speech Sciences
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• v.9 no.1
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• pp.41-47
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• 2017

The main advantage of the statistical parametric speech synthesis is its flexibility in changing voice characteristics. A personalized text-to-speech(TTS) system can be implemented by combining a speech synthesis system and a voice transformation system, and it is widely used in many application areas. It is known that the fundamental frequency and the spectral envelope of speech signal can be independently modified to convert the voice characteristics. Also it is important to maintain naturalness of the transformed speech. In this paper, a speech synthesis system based on Hidden Markov Model(HMM-based speech synthesis, HTS) using the STRAIGHT vocoder is constructed and voice transformation is conducted by modifying the fundamental frequency and spectral envelope. The fundamental frequency is transformed in a scaling method, and the spectral envelope is transformed through frequency warping method to control the speaker's vocal tract length. In particular, this study proposes a voice transformation method using the correlation between fundamental frequency and vocal tract length. Subjective evaluations were conducted to assess preference and mean opinion scores(MOS) for naturalness of synthetic speech. Experimental results showed that the proposed voice transformation method achieved higher preference than baseline systems while maintaining the naturalness of the speech quality.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.5
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• pp.123-130
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• 2001

The purpose of this paper is to reduce the level of idling vibration on a steering wheel. In some cases, vibration on steering wheel is amplified due to the resonance between the first natural frequency of T-beam and engine idling speed. Using SDM(structural dynamic modification) technique, T-beam is redesigned to reduce its vibration. This paper used FRF(frequency response function) synthesis technique which is entirely dependent on experiment. But this method requires lots of test efforts to enhance its reliability of design. While combining this method with an analytic method. the experimental burden, the major drawback of FRP synthesis method, can be considerably relieved. Using ana1ytic sensitivity analysis, some effective modification regions are preliminarily chosen as candidate Positions where SDM can be applied to modify T-beam\`s dynamic characteristics.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.1
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• pp.34-40
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• 2005

This paper presents a frequency transfer function synthesis for simplifying a high-order model with time delay to a low-order model. A model reduction is based on minimizing the error function weighted by the numerator polynomial of reduced systems. The proposed method provides better low frequency fit and a computer aided algorithm. And in this paper, we present a design method of PID controller for achieving the desired specifications via the reduced model. The proposed method identifies the parameter vector of PID controller from a linear system that develops from rearranging the two dimensional input matrices and output vectors obtained from the frequency bounds.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.713-725
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• 2022

Mostly, artificial intelligence does not show any definite change in emotions. For this reason, it is hard to demonstrate empathy in communication with humans. If frequency modification is applied to neutral emotions, or if a different emotional frequency is added to them, it is possible to develop artificial intelligence with emotions. This study proposes the emotion conversion using the Generative Adversarial Network (GAN) based voice frequency synthesis. The proposed method extracts a frequency from speech data of twenty-four actors and actresses. In other words, it extracts voice features of their different emotions, preserves linguistic features, and converts emotions only. After that, it generates a frequency in variational auto-encoding Wasserstein generative adversarial network (VAW-GAN) in order to make prosody and preserve linguistic information. That makes it possible to learn speech features in parallel. Finally, it corrects a frequency by employing Amplitude Scaling. With the use of the spectral conversion of logarithmic scale, it is converted into a frequency in consideration of human hearing features. Accordingly, the proposed technique provides the emotion conversion of speeches in order to express emotions in line with artificially generated voices or speeches.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.57-66
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• 2006

In this paper, I propose a new method of Multi-Pulse Speech Coding(FBD-MPC: Frequency Band Division MPC) by using TSIUVC(Transition Segment Including UnVoiced Consonant) searching, extraction and approximation-synthesis method in a frequency domain. As, a result. the extraction rates of TSIUVC are 84.8%(plosive), 94.9%(fricative) and 92.3%(affricative) in female voice, 88%(plosive), 94.9%(fricative) and 92.3%(affricative) in male voice respectively. Also, I obtain a high quality approximation-synthesis waveforms within TSIUVC by using frequency information of 0.547kHz below and 2.813kHz above. I evaluate MPC by using switching information of voiced/unvoiced and FBD-MPC by using switching information of voiced/Silence/TSIUVC. As, a result, I knew that synthesis speech of FBD-MPC was better in speech quality than synthesis speech of the MPC.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.649-654
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• 2002

The essential philosophy of the QFT(Quantitative Feedback Theory) is that a suitable controller can be found by loop shaping a nominal loop transfer function such that the frequency response of this function does not violate the QFT bounds. The loop shaping synthesis involves the identification of a structure and its specialization by means of the parameter optimization. This paper presents an optimization algorithm to estimate the controller parameters from the frequency transfer function synthesis using the TLS(Total Least Squares) in the QFT loop shaping procedure. The proposed method identifies the parameter vector of the robust controller from an overdetermined linear system developed from rearranging the two dimensional system matrices and output vectors obtained from the QFT bounds. The feasibility of the suggested algorithm is illustrated with an example.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.9
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• pp.88-93
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• 2008

This paper proposes a frequency transfer function synthesis of a later compensated PID controller for an approximated low order model. The proposed method identifies the parameter vector of PID controller from a linear system that is formed by rearranging a loop frequency transfer function synthesis including the filter compensated PID controller obtained from the given frequency response bounds. And an example for the turbine speed control system of Chungju hydropower plant is given to illustrate the feasibilities of suggested schemes.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.24-38
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• 1994

In this paper we develop the software simulator written in a C language for a frequency modulation synthesis and the approximate range of parameters, for a musically satisfactory timbre, obtained by using the software simulator will be applied to develop an algorithm for parameter extraction. For a frequency modulation synthesis, we also develop an algorithm for parameter extraction through waveform analysis in the time domain as well as spectrum analysis using a FFT in the frequency domain. To verify the validity of the developed algorithm as well as software simulator experimentally, we extract parameters for the several music instruments using the suggested algorithm and analyze the synthesized sound by applying the parameters to the software simulator. The evaluation of the synthesized sound is first done by listening the sound directly as a subjective testing. Secondly, to evaluate the synthesized sound objectively with an engineering sense, we compare the synthesized sound with an original one in a time domain and a frequency domain.