• 제목/요약/키워드: Spectral matching

검색결과 123건 처리시간 0.022초

코퍼스 기반 음성합성기를 위한 합성단위 경계 스펙트럼 평탄화 알고리즘 (A Spectral Smoothing Algorithm for Unit Concatenating Speech Synthesis)

  • 김상진;장경애;한민수
    • 대한음성학회지:말소리
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    • 제56호
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    • pp.225-235
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    • 2005
  • Speech unit concatenation with a large database is presently the most popular method for speech synthesis. In this approach, the mismatches at the unit boundaries are unavoidable and become one of the reasons for quality degradation. This paper proposes an algorithm to reduce undesired discontinuities between the subsequent units. Optimal matching points are calculated in two steps. Firstly, the fullback-Leibler distance measurement is utilized for the spectral matching, then the unit sliding and the overlap windowing are used for the waveform matching. The proposed algorithm is implemented for the corpus-based unit concatenating Korean text-to-speech system that has an automatically labeled database. Experimental results show that our algorithm is fairly better than the raw concatenation or the overlap smoothing method.

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원본 지반운동 시간이력에 따른 스펙트럼 부합 시간이력의 특성 (Characteristics of Spectral Matched Ground Motions Time Histories According to Seed Ground Motion Selection)

  • 최다슬;지혜연;김정한
    • 한국지진공학회논문집
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    • 제25권1호
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    • pp.43-52
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    • 2021
  • According to several seismic design standards, a ground motion time history should be selected similar to the design response spectrum, or a ground motion time history should be modified by matching procedure to the design response spectrum through the time-domain method. For the response spectrum matching procedure, appropriate seed ground motions need to be selected to maintain recorded earthquake accelerogram characteristics. However, there are no specific criteria for selecting the seed ground motions for applying this methodology. In this study, the characteristics of ground motion time histories between seed motions and spectral matched motions were compared. Intensity measures used in the design were compared, and their change by spectral matching procedure was quantified. In addition, the seed ground motion sets were determined according to the response spectrum shape, and these sets analyzed the response of nonlinear and equivalent linear single degrees of freedom systems to present the seed motion selection conditions for spectral matching. As a result, several considerations for applying the time domain spectral matching method were presented.

Noisy Band Removal Using Band Correlation in Hyperspectral lmages

  • Huan, Nguyen Van;Kim, Hak-Il
    • 대한원격탐사학회지
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    • 제25권3호
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    • pp.263-270
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    • 2009
  • Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

A𝛼-SPECTRAL EXTREMA OF GRAPHS WITH GIVEN SIZE AND MATCHING NUMBER

  • Xingyu Lei;Shuchao Li;Jianfeng Wang
    • 대한수학회보
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    • 제60권4호
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    • pp.873-893
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    • 2023
  • In 2017, Nikiforov proposed the A𝛼-matrix of a graph G. This novel matrix is defined as A𝛼(G) = 𝛼D(G) + (1 - 𝛼)A(G), 𝛼 ∈ [0, 1], where D(G) and A(G) are the degree diagonal matrix and adjacency matrix of G, respectively. Recently, Zhai, Xue and Liu [39] considered the Brualdi-Hoffman-type problem for Q-spectra of graphs with given matching number. As a continuance of it, in this contribution we consider the Brualdi-Hoffman-type problem for A𝛼-spectra of graphs with given matching number. We identify the graphs with given size and matching number having the largest A𝛼-spectral radius for ${\alpha}{\in}[{\frac{1}{2}},1)$.

Study of Spectral Reflectance Reconstruction Based on an Algorithm for Improved Orthogonal Matching Pursuit

  • Leihong, Zhang;Dong, Liang;Dawei, Zhang;Xiumin, Gao;Xiuhua, Ma
    • Journal of the Optical Society of Korea
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    • 제20권4호
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    • pp.515-523
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    • 2016
  • Spectral reflectance is sparse in space, and while the traditional spectral-reconstruction algorithm does not make full use of this characteristic sparseness, the compressive sensing algorithm can make full use of it. In this paper, on the basis of analyzing compressive sensing based on the orthogonal matching pursuit algorithm, a new algorithm based on the Dice matching criterion is proposed. The Dice similarity coefficient is introduced, to calculate the correlation coefficient of the atoms and the residual error, and is used to select the atoms from a library. The accuracy of Spectral reconstruction based on the pseudo-inverse method, Wiener estimation method, OMP algorithm, and DOMP algorithm is compared by simulation on the MATLAB platform and experimental testing. The result is that spectral-reconstruction accuracy based on the DOMP algorithm is higher than for the other three methods. The root-mean-square error and color difference decreases with an increasing number of principal components. The reconstruction error decreases as the number of iterations increases. Spectral reconstruction based on the DOMP algorithm can improve the accuracy of color-information replication effectively, and high-accuracy color-information reproduction can be realized.

FREQUENCY SELECTIVE RECURSIVE LP OF HARMONIC SPECTRA

  • SeungHyonNam
    • 지구물리
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    • 제4권4호
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    • pp.231-238
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    • 2001
  • In this paper, an efficient LP method ofr discrete harmonic spectra is proposed and discussed. A new efficient LP method is a combination of recursive and frequency selective LP. While the recursive LP provides better spectral matching in spectral hills, frequency selective LP eliminates numerical instability and improves spectral matching when the harmonics are confined in the low frequncy region. The proposed LP method is applied to the HILN coder. Simulation results using a verification model(VM) software for real audio signals show a definite trend of significant improvement.

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Frequency Selective Recursive LP of Discrete Harmonic Spectra for Audio Cording

  • Nam, Seung-Hyon
    • 공학논문집
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    • 제5권1호
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    • pp.37-44
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    • 2004
  • n this paper, an efficient LP method for discrete harmonic spectra is proposed and discussed. A new efficient LP method is a combination of recursive and frequency selective LP. While the recursive LP provides better spectral matching in spectral hill, frequency selective LP eliminates numerical instability and improves spectral matching when the harmonics are confined in the low frequency region. The proposed LP method is applied to the HILN coder. Simulation results using a verification model(VM) software for real audio signals show a definite trend of significant improvement.

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공간 영상 처리를 위한 SIFT 매칭 기법의 성능 분석 (A Performance Analysis of the SIFT Matching on Simulated Geospatial Image Differences)

  • 오재홍;이효성
    • 한국측량학회지
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    • 제29권5호
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    • pp.449-457
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    • 2011
  • As automated image processing techniques have been required in multi-temporal/multi-sensor geospatial image applications, use of automated but highly invariant image matching technique has been a critical ingredient. Note that there is high possibility of geometric and spectral differences between multi-temporal/multi-sensor geospatial images due to differences in sensor, acquisition geometry, season, and weather, etc. Among many image matching techniques, the SIFT (Scale Invariant Feature Transform) is a popular method since it has been recognized to be very robust to diverse imaging conditions. Therefore, the SIFT has high potential for the geospatial image processing. This paper presents a performance test results of the SIFT on geospatial imagery by simulating various image differences such as shear, scale, rotation, intensity, noise, and spectral differences. Since a geospatial image application often requires a number of good matching points over the images, the number of matching points was analyzed with its matching positional accuracy. The test results show that the SIFT is highly invariant but could not overcome significant image differences. In addition, it guarantees no outlier-free matching such that it is highly recommended to use outlier removal techniques such as RANSAC (RANdom SAmple Consensus).

STATISTICAL NOISE BAND REMOVAL FOR SURFACE CLUSTERING OF HYPERSPECTRAL DATA

  • Huan, Nguyen Van;Kim, Hak-Il
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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    • pp.111-114
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    • 2008
  • The existence of noise bands may deform the typical shape of the spectrum, making the accuracy of clustering degraded. This paper proposes a statistical approach to remove noise bands in hyperspectral data using the correlation coefficient of bands as an indicator. Considering each band as a random variable, two adjacent signal bands in hyperspectral data are highly correlative. On the contrary, existence of a noise band will produce a low correlation. For clustering, the unsupervised ${\kappa}$-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID. Furthermore, this paper proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures.

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정현파 모델 부호화기를 위한 MP(Matching Pursuit) 알고리즘과 파라미터 양자화기 (Matching Pursuit Estimation and Quantizer Design for Sinusoidal Model-based Coder)

  • 안영욱;정규혁;김종학;양용호;이인성
    • 한국음향학회지
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    • 제24권7호
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    • pp.402-409
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    • 2005
  • 본 논문에서는 고대역 (4kHz-8kHz)의 주기적 성분이 강하게 나타나는 신호에 대해서 MP (Matching Pursuit) 알고리즘을 이용한 부호화 방법을 제안한다. 또한 분석된 스펙트럼 크기 파라미터와 위상 파라미터의 효율적인 양자화 방법을 제안한다. MP 알고리즘은 오류 상쇄 원리와 정현파 모델에 바탕을 두고 있기 때문에 정확한 피치 주기 예측이 필요하다. 고대역의 정확한 피치 주기 예측을 위해 저대역 (0kHz-4kHz) 신호에서 검출한 피치 주기를 이용함으로써 부호화와 비트할당의 효율을 높일 수 있다. 스펙트럼 크기 계수의 양자화를 위해 계수들에 대해 고정 차원 이산코사인 변환 (MDCT : Modified Discrete Cosine Transform) 및 다단계 (multi-stage) 구조를 결합시킨 양자화 기법을 사용하였고, 위상 값들은 스펙트럼 크기에 따른 가중치 필터와 위상의 $2{\pi}$ 순환 특성을 이용하여 양자화하였다. 또한 제안한 양자화 기법과 부호화 방법을 음성 분석-합성 (analysis-by-synthesis) 시스템에 적용하여, 목적 신호와의 비교를 통해 검증한다. 향후 대역 분할을 기본 구조로 하는 계층 구조의 광대역 음성부호화기에의 적용 가능성을 제시한다.