• 제목/요약/키워드: power normalization

검색결과 105건 처리시간 0.031초

파워 스펙트럼 warping을 이용한 성도 정규화 (Vocal Tract Normalization Using The Power Spectrum Warping)

  • 유일수;김동주;노용완;홍광석
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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    • pp.215-218
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    • 2003
  • The method of vocal tract normalization has been known as a successful method for improving the accuracy of speech recognition. A frequency warping procedure based low complexity and maximum likelihood has been generally applied for vocal tract normalization. In this paper, we propose a new power spectrum warping procedure that can be improve on vocal tract normalization performance than a frequency warping procedure. A mechanism for implementing this method can be simply achieved by modifying the power spectrum of filter bank in Mel-frequency cepstrum feature(MFCC) analysis. Experimental study compared our Proposal method with the well-known frequency warping method. The results have shown that the power spectrum warping is better 50% about the recognition performance than the frequency warping.

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화자 정규화를 위한 새로운 파워 스펙트럼 Warping 방법 (A New Power Spectrum Warping Approach to Speaker Warping)

  • 유일수;김동주;노용완;홍광석
    • 대한전자공학회논문지SP
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    • 제41권4호
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    • pp.103-111
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    • 2004
  • 화자 정규화 방법은 화자 독립 음성인식 시스템에서 음성 인식의 정확성을 높이기 위한 성공적인 방법으로 알려져 왔다. 널리 사용되는 화자 정규화 방법은 maximum likelihood 반의 주파수 warping 방법이다. 본 논문은 주파수 warping 보다 더 좋은 화자 정규화의 성능 개선을 위해 새로운 파워 스펙트럼 warping 방법을 제안한다. 파워 스펙트럼 warping은 멜 주파수 켑스트럼 분석(MFCC) 방법을 이용하며, MFCC 처리 단계에서 필터 뱅크의 파워 스펙트럼을 조절함으로써 화자 정규화를 수행하는 간단한 메커니즘으로 갖는다. 또한 본 논문은 파워 스펙트럼 warping과 주파수 warping 방법을 서로 결합한 hybrid VTN 방법을 제안한다. 본 논문의 실험은 baseline 시스템에 각 화자 정규화 방법을 적용하여 SKKU PBW DB에서 인식 성능을 비교 분석하였다. 실험 결과를 보면 baseline 시스템의 단어 인식 성능을 기준으로 주파수 warping은 2.06%, 파워 스펙트럼 warping은 3.05%, 그리고 hybrid VTN은 4.07%의 단어 에러 율의 감소를 보였다.

On the Signal Power Normalization Approach to the Escalator Adaptive filter Algorithms

  • Kim Nam-Yong
    • 한국통신학회논문지
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    • 제31권8C호
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    • pp.801-805
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    • 2006
  • A normalization approach to coefficient adaptation in the escalator(ESC) filter structure that conventionally employs least mean square(LMS) algorithm is introduced. Using Taylor's expansion of the local error signal, a normalized form of the ESC-LMS algorithm is derived. Compared with the computational complexity of the conventional ESC-LMS algorithm employs input power estimation for time-varying convergence coefficient using a single-pole low-pass filter, the computational complexity of the proposed method can be reduced by 50% without performance degradation.

Online Blind Channel Normalization Using BPF-Based Modulation Frequency Filtering

  • Lee, Yun-Kyung;Jung, Ho-Young;Park, Jeon Gue
    • ETRI Journal
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    • 제38권6호
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    • pp.1190-1196
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    • 2016
  • We propose a new bandpass filter (BPF)-based online channel normalization method to dynamically suppress channel distortion when the speech and channel noise components are unknown. In this method, an adaptive modulation frequency filter is used to perform channel normalization, whereas conventional modulation filtering methods apply the same filter form to each utterance. In this paper, we only normalize the two mel frequency cepstral coefficients (C0 and C1) with large dynamic ranges; the computational complexity is thus decreased, and channel normalization accuracy is improved. Additionally, to update the filter weights dynamically, we normalize the learning rates using the dimensional power of each frame. Our speech recognition experiments using the proposed BPF-based blind channel normalization method show that this approach effectively removes channel distortion and results in only a minor decline in accuracy when online channel normalization processing is used instead of batch processing

CONTINUATION THEOREMS OF THE EXTREMES UNDER POWER NORMALIZATION

  • Barakat, H.M.;Nigm, E.M.;El-Adll, M.E.
    • Journal of applied mathematics & informatics
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    • 제10권1_2호
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    • pp.1-15
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    • 2002
  • In this paper an important stability property of the extremes under power normalizations is discussed. It is proved that the restricted convergence of the Power normalized extremes on an arbitrary nondegenerate interval implies the weak convergence. Moreover, this implication, in an important practical situation, is obtained when the sample size is considered as a random variable distributed geometrically with mean n.

저전력 및 면적 효율적인 터보 복호기를 위한 정규화 유닛 설계 (Design of the Normalization Unit for a Low-Power and Area-Efficient Turbo Decoders)

  • 문제우;김식;황선영
    • 한국통신학회논문지
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    • 제28권11C호
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    • pp.1052-1061
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    • 2003
  • 본 논문은 블록 MAP 터보 복호기의 상태 메트릭 계산 유닛을 위한 정규화 방식을 제안한다. 제안된 방식은 정규화를 위해 격자단(trellis stage)에서 하나의 상태 메트릭 값을 모든 상태 메트릭에 빼주고 쉬프트 시키는 구조를 갖게 되어, 상태 메트릭 계산이 많은 블록 MAP 복호기의 격자단에서 하나의 상태 메트릭을 줄여 파워 소모와 메모리 요구량을 줄일 수 있다. 시뮬레이션 결과 제안된 정규화 구조를 적용한 터보 복호기는 기존의 블록 MAP 터보 복호기에 비해 동적 파워 소모는 17.9%까지 감소하고 면적은 6.6%까지 감소함을 확인하였다.

Semi-supervised Software Defect Prediction Model Based on Tri-training

  • Meng, Fanqi;Cheng, Wenying;Wang, Jingdong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권11호
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    • pp.4028-4042
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    • 2021
  • Aiming at the problem of software defect prediction difficulty caused by insufficient software defect marker samples and unbalanced classification, a semi-supervised software defect prediction model based on a tri-training algorithm was proposed by combining feature normalization, over-sampling technology, and a Tri-training algorithm. First, the feature normalization method is used to smooth the feature data to eliminate the influence of too large or too small feature values on the model's classification performance. Secondly, the oversampling method is used to expand and sample the data, which solves the unbalanced classification of labelled samples. Finally, the Tri-training algorithm performs machine learning on the training samples and establishes a defect prediction model. The novelty of this model is that it can effectively combine feature normalization, oversampling techniques, and the Tri-training algorithm to solve both the under-labelled sample and class imbalance problems. Simulation experiments using the NASA software defect prediction dataset show that the proposed method outperforms four existing supervised and semi-supervised learning in terms of Precision, Recall, and F-Measure values.

Scaling of design earthquake ground motions for tall buildings based on drift and input energy demands

  • Takewaki, I.;Tsujimoto, H.
    • Earthquakes and Structures
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    • 제2권2호
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    • pp.171-187
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    • 2011
  • Rational scaling of design earthquake ground motions for tall buildings is essential for safer, risk-based design of tall buildings. This paper provides the structural designers with an insight for more rational scaling based on drift and input energy demands. Since a resonant sinusoidal motion can be an approximate critical excitation to elastic and inelastic structures under the constraint of acceleration or velocity power, a resonant sinusoidal motion with variable period and duration is used as an input wave of the near-field and far-field ground motions. This enables one to understand clearly the relation of the intensity normalization index of ground motion (maximum acceleration, maximum velocity, acceleration power, velocity power) with the response performance (peak interstory drift, total input energy). It is proved that, when the maximum ground velocity is adopted as the normalization index, the maximum interstory drift exhibits a stable property irrespective of the number of stories. It is further shown that, when the velocity power is adopted as the normalization index, the total input energy exhibits a stable property irrespective of the number of stories. It is finally concluded that the former property on peak drift can hold for the practical design response spectrum-compatible ground motions.

TLC/HPTLC에서 측정된 자외/가시부 스펙트럼의 표준화 및 검색 (Normalization and Search of the UV/VIS Spectra Measured from TLC/HPTLC)

  • 강종성
    • 약학회지
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    • 제38권4호
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    • pp.366-371
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    • 1994
  • To improve the identification power of TLC/HPTLC the in situ reflectance spectra obtained directly from plates with commercial scanner are used. The spectrum normalization should be carried out prior to comparing and searching the spectra from library for the identification of compounds. Because the reflectance does not obey the Lambert-Beer's law, there arise some problems in normalization. These problems could be solved to some extent by normalizing the spectra with regression methods. The spectra are manipulated with the regression function of a curve obtained from the correlation plot. When the parabola was used as the manipulating function, the spectra were identified with the accuracy of 97% and this result was better than that of conventionally used the point and area normalization method.

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3-level 계층 64QAM 기법의 정규화 인수 (Normalization Factor for Three-Level Hierarchical 64QAM Scheme)

  • 유동호;김동호
    • 한국통신학회논문지
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    • 제41권1호
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    • pp.77-79
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    • 2016
  • 본 논문에서는 디지털 방송시스템의 전송방식에서 널리 사용 되고 있는 계층 변조 (Hierarchical Modulation)를 고려한다. 계층 변조기법은 다수의 독립적인 데이터 스트림의 송신 신호 전력을 조절하여 변조 심볼로 매핑하기 때문에 종래의 M-QAM에서 사용하는 정규화 인수 (Normalization Factor)를 사용할 수 없다. 본 논문에서는 3-level 계층 64QAM 기법의 정확한 정규화 인수를 구하기 위한 방법과 과정을 유도하여 제시한다.