• 제목/요약/키워드: synthesis models

검색결과 347건 처리시간 0.026초

ANN Synthesis Models Trained with Modified GA-LM Algorithm for ACPWs with Conductor Backing and Substrate Overlaying

  • Wang, Zhongbao;Fang, Shaojun;Fu, Shiqiang
    • ETRI Journal
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    • 제34권5호
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    • pp.696-705
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    • 2012
  • Accurate synthesis models based on artificial neural networks (ANNs) are proposed to directly obtain the physical dimensions of an asymmetric coplanar waveguide with conductor backing and substrate overlaying (ACPWCBSO). First, the ACPWCBSO is analyzed with the conformal mapping technique (CMT) to obtain the training data. Then, a modified genetic-algorithm-Levenberg-Marquardt (GA-LM) algorithm is adopted to train ANNs. In the algorithm, the maximal relative error (MRE) is used as the fitness function of the chromosomes to guarantee that the MRE is small, while the mean square error is used as the error function in LM training to ensure that the average relative error is small. The MRE of ANNs trained with the modified GA-LM algorithm is less than 8.1%, which is smaller than those trained with the existing GA-LM algorithm and the LM algorithm (greater than 15%). Lastly, the ANN synthesis models are validated by the CMT analysis, electromagnetic simulation, and measurements.

HMM 기반의 한국어 음성합성에서 음색변환에 관한 연구 (A Study on the Voice Conversion with HMM-based Korean Speech Synthesis)

  • 김일환;배건성
    • 대한음성학회지:말소리
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    • 제68권
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    • pp.65-74
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    • 2008
  • A statistical parametric speech synthesis system based on the hidden Markov models (HMMs) has grown in popularity over the last few years, because it needs less memory and low computation complexity and is suitable for the embedded system in comparison with a corpus-based unit concatenation text-to-speech (TTS) system. It also has the advantage that voice characteristics of the synthetic speech can be modified easily by transforming HMM parameters appropriately. In this paper, we present experimental results of voice characteristics conversion using the HMM-based Korean speech synthesis system. The results have shown that conversion of voice characteristics could be achieved using a few sentences uttered by a target speaker. Synthetic speech generated from adapted models with only ten sentences was very close to that from the speaker dependent models trained using 646 sentences.

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수중 반사신호 합성을 위한 표적강도 예측모델 비교분석 (A Comparative Analysis of Target Strength Estimated Models for Underwater Echo Signal Synthesis)

  • 김부일
    • 한국군사과학기술학회지
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    • 제4권1호
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    • pp.93-103
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    • 2001
  • 고주파를 주로 사용하는 능동소나에서 반사신호는 물체표면의 거울면 반사와 내부의 여러 등가적인 산란자로 형성되며, 이는 물체에 공간적으로 분포된 하이라이트에 의해 특징 된다. 본 연구에서는 기존의 모의표적에 대한 반사신호 합성모델 즉, 랜덤분포 모델, 등간격분포 모델 및 MUTAHID 모델에 대하여 분석하고, 합성된 반사신호 결과특성을 여러 조건에서 비교하였다. 이러한 하이라이트 분포 모델들은 수중표적의 반사신호 합성을 필요로 하는 각종 실시스템의 모의표적 신호 합성에 유용하게 적용될 수 있으리라 생각된다.

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Perceptual Evaluation of Duration Models in Spoken Korean

  • Chung, Hyun-Song
    • 음성과학
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    • 제9권1호
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    • pp.207-215
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    • 2002
  • Perceptual evaluation of duration models of spoken Korean was carried out based on the Classification and Regression Tree (CART) model for text-to-speech conversion. A reference set of durations was produced by a commercial text-to-speech synthesis system for comparison. The duration model which was built in the previous research (Chung & Huckvale, 2001) was applied to a Korean language speech synthesis diphone database, 'Hanmal (HN 1.0)'. The synthetic speech produced by the CART duration model was preferred in the subjective preference test by a small margin and the synthetic speech from the commercial system was superior in the clarity test. In the course of preparing the experiment, a labeled database of spoken Korean with 670 sentences was constructed. As a result of the experiment, a trained duration model for speech synthesis was obtained. The 'Hanmal' diphone database for Korean speech synthesis was also developed as a by-product of the perceptual evaluation.

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역할-거동 모델링에 기반한 화학공정 이상 진단을 위한 이상-인과 그래프 모델의 합성 (Synthesis of the Fault-Causality Graph Model for Fault Diagnosis in Chemical Processes Based On Role-Behavior Modeling)

  • 이동언;어수영;윤인섭
    • 제어로봇시스템학회논문지
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    • 제10권5호
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    • pp.450-457
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    • 2004
  • In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

Human Laughter Generation using Hybrid Generative Models

  • Mansouri, Nadia;Lachiri, Zied
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권5호
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    • pp.1590-1609
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    • 2021
  • Laughter is one of the most important nonverbal sound that human generates. It is a means for expressing his emotions. The acoustic and contextual features of this specific sound are different from those of speech and many difficulties arise during their modeling process. During this work, we propose an audio laughter generation system based on unsupervised generative models: the autoencoder (AE) and its variants. This procedure is the association of three main sub-process, (1) the analysis which consist of extracting the log magnitude spectrogram from the laughter database, (2) the generative models training, (3) the synthesis stage which incorporate the involvement of an intermediate mechanism: the vocoder. To improve the synthesis quality, we suggest two hybrid models (LSTM-VAE, GRU-VAE and CNN-VAE) that combine the representation learning capacity of variational autoencoder (VAE) with the temporal modelling ability of a long short-term memory RNN (LSTM) and the CNN ability to learn invariant features. To figure out the performance of our proposed audio laughter generation process, objective evaluation (RMSE) and a perceptual audio quality test (listening test) were conducted. According to these evaluation metrics, we can show that the GRU-VAE outperforms the other VAE models.

Complex Discrete Systems Graph Simulation

  • Kadirova, Delovar;Kadirova, Aziza
    • Journal of Multimedia Information System
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    • 제2권3호
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    • pp.263-274
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    • 2015
  • The subject of this work is the complex discrete systems simulation special features with the aid of dynamic graph models. The proposed simulation technique allows to determine the ways for tasks solutions in terms of discrete systems analysis and synthesis of various complication: one-dimensional and multidimensional, steady and unstable, with the pulse elements abnormal operating mode and others. Often complex control systems analysis and synthesis task solutions, via classical approach comes out to be insolvent, because of the computational problems. The application of graph models allows to perform clear and strict characterization and computer procedures automation. The optimal controls synthesis algorithm presented in this paper, transferring the discrete system from target initial state to target final state within the minimum time, allows to consider the zero initial conditions systems, with the initial potential energy, with the control actions limitations and complex pulse elements operating mode.

부분 구조 모드 합성법 및 유전 전략 최적화 기법을 이용한 비부합 절점을 가진 구조물의 구조변경 (Structural Dynamics Modification of Structures Having Non-Conforming Nodes Using Component Mode Synthesis and Evolution Strategies Optimization Technique)

  • 이준호;정의일;박윤식
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2002년도 춘계학술대회논문집
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    • pp.651-659
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    • 2002
  • Component Mode Synthesis (CMS) is a dynamic substructuring technique to get an approximate eigensolutions of large degree-of-freedom structures divisible into several components. But, In practice. most of large structures are modeled by different teams of engineers. and their respective finite element models often require different mesh resolutions. As a result, the finite element substructure models can be non-conforming and/or incompatible. In this work, A hybrid version of component mode synthesis using a localized lagrange multiplier to treat the non-conforming mesh problem was derived. Evolution Strategies (ESs) is a stochastic numerical optimization technique and has shown a robust performance for solving deterministic problems. An ESs conducts its search by processing a population of solutions for an optimization problem based on principles from natural evolution. An optimization example for raising the first natural frequency of a plate structure using beam stiffeners was presented using hybrid component mode synthesis and robust evolution strategies (RES) optimization technique. In the example. the design variables are the positions and lengths of beam stiffeners.

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AGES OF ELLIPTICAL GALAXIES FROM POPULATION SYNTHESIS MODELS

  • LEE YOUNG-WOOK;PARK JANG-HYUN
    • 천문학회지
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    • 제29권spc1호
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    • pp.49-51
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    • 1996
  • New population synthesis models, with the effects of metallicity spread and the horizontal-branch (HB) morphology, provide a way to break the well-known age-metallicity degeneracy in the analysis of the integrated light of elliptical galaxies. Our models suggest that the far- UV radiation of these systems is dominated by a minority population of metal-poor, hot HB stars and their post-HB progeny, while the optical radiation is dominated by a metal-rich population. The systematic variation of UV upturn depends on the contribution from metal-poor, hot HB stars and their post-HB progeny, which in turn depends on the ages of old stellar populations in galaxies. Our result implies a prolonged epoch of galaxy formation, in the sense that more massive galaxies (in denser environments) formed first. Our models also suggest that the strenghth of H$\beta$ index is strongly affected by HB stars, and hence previous age estimation without detailed modeling of the HB would underestimate the ages of ellipticals by $\~$7 Gyr.

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집중 질량-스프링 모델을 이용한 볼트 결합부 모델링 (Dynamic Modeling of Bolt Joints Using Lumped Mass-Spring Model)

  • 고강호;이장무
    • 대한기계학회논문집A
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    • 제25권3호
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    • pp.495-501
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    • 2001
  • In this paper, a new technique which models the joints characteristics through reduction of DOFs of structures with joints using component mode synthesis (CMS) method is proposed. Bolt joints are modeled by mass-spring systems. Also generalized mass and stiffness matrices for this models are introduced. Because bolt joints have influence on eigenvalues of structures, exact eigenvalues from modal test are used. The results show that the behaviors of structures with bolt joints depend to a large extent on the translational DOFs and not on rotational DOFs of mass and stiffness matrices of bolts. Furthermore it is confirmed that lumped mass-spring systems as models of bolt joints are effective models considering the facts that joint characteristics converged to constant values in some iterations and eignevalues from proposed method are in good agreement with ones from modal test.