• The Journal of the Acoustical Society of Korea
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• v.10 no.4
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• pp.27-37
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• 1991

This paper proposes the ESFVQ(energy subspace fuzzy vector quantization) that employs energy subspaces to reduce the quantizing distortion which is less than that of a fuzzy vector quatization. The ESFVQ is applied to a speaker adaptation method by which Korean words spoken by unknown speakers are recognized. By generating mapped codebooks with fuzzy histogram according to each energy subspace in the training procedure and by decoding a spoken word through the ESFVQ in the recognition proecedure, we attempt to improve the recognition rate. The performance of the ESFVQ is evaluated by measuring the quantizing distortion and the speaker adaptive recognition rate for DDD telephone area names uttered by 2 males and 1 female. The quatizing distortion of the ESFVQ is reduced by 22% than that of a vector quantization and by 5% than that of a fuzzy vector quantization, and the speaker adaptive recognition rate of the ESFVQ is increased by 26% than that without a speaker adaptation and by 11% than that of a vector quantization.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.91-95
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• 2004

In this paper, we propose a fuzzy controller for the evaluation of the quantization parameters in the H.263 coder. Our method adopts the Mamdani method for fuzzification and adopts the centroid method for defuzzification respectively. The inputs are variance, entropy in the spatial domain, current motion vector and previous motion vector in the temporal. Fuzzy variables are determined to be compatible in visual characteristics and fuzzy membership function is induced and then, FAM banks are designed to reduce the number of rules. In this paper, fuzzy quantization has been applied to a practical video compression. This results show that the quality of decode image enhances and the rate control method using fuzzy quantization is effective.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.60-69
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• 1998

This paper proposes a speech synthesis method using Fuzzy VQ, and then study how to make choice of fuzziness value which optimizes (controls) the performance of FVQ in order to obtain the synthesized speech which is closer to the original speech. When FVQ is used to synthesize a speech, analysis stage generates membership function values which represents the degree to which an input speech pattern matches each speech patterns in codebook, and synthesis stage reproduces a synthesized speech, using membership function values which is obtained in analysis stage, fuzziness value, and fuzzy-c-means operation. By comparsion of the performance of the FVQ and VQ synthesizer with simmulation, we show that, although the FVQ codebook size is half of a VQ codebook size, the performance of FVQ is almost equal to that of VQ. This results imply that, when Fuzzy VQ is used to obtain the same performance with that of VQ in speech synthesis, we can reduce by half of memory size at a codebook storage. And then we have found that, for the optimized FVQ with maximum SQNR in synthesized speech, the fuzziness value should be small when the variance of analysis frame is relatively large, while fuzziness value should be large, when it is small. As a results of comparsion of the speeches synthesized by VQ and FVQ in their spectrogram of frequency domain, we have found that spectrum bands(formant frequency and pitch frequency) of FVQ synthesized speech are closer to the original speech than those using VQ.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1684-1690
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• 2003

In this paper, we proposed a fuzzy controller for the evaluation of the quantization Parameters in the H.263 coder to optimize the subjective quality of each coded frame, keeping the transmission rate constant. We adopted the Mamdani method for fuzzification and the centroid method for defuzzification. The energy and entropy are correlated to features of the HVS in spatial domain, while motion vectors are used to estimate the temporal characteristics of the signal. And then, the fuzzy inputs adapted the variance and the entropy in spatial domain, and the motion vector in temporal domain. We induced the fuzzy membership function and decided the fuzzy relevance to be compatible in visual characteristics. And then, we designed FAM banks. The fuzzy technology has been applied to a practical video compression. This results is obtained an effective rate control technique, an optimum bit allocation and a high subjective quality using fuzzy quantization.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.411-418
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• 2009

Vector quantization algorithm based on fuzzy clustering has been widely used in the field of data compression since the use of fuzzy clustering analysis in the early stages of a vector quantization process can make this process less sensitive to its initialization. However, the process of fuzzy clustering is computationally very intensive because of its complex framework for the quantitative formulation of the uncertainty involved in the training vector space. To overcome the computational burden of the process, this paper introduces an array architecture for the implementation of fuzzy vector quantization (FVQ). The arrayarchitecture, which consists of 4,096 processing elements (PEs), provides a computationally efficient solution by employing an effective vector assignment strategy during the clustering process. Experimental results indicatethat the proposed parallel implementation providessignificantly greater performance and efficiency than appropriately scaled alternative array systems. In addition, the proposed parallel implementation provides 1000x greater performance and 100x higher energy efficiency than other implementations using today's ARMand TI DSP processors in the same 130nm technology. These results demonstrate that the proposed parallel implementation shows the potential for improved performance and energy efficiency.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.149-160
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• 1997

This paper is concerned with the problem of speaker-adaptive speech synthes is method using a mapped codebook designed by fuzzy mapping on FLVQ (Fuzzy Learning Vector Quantization). The FLVQ is used to design both input and reference speaker's codebook. This algorithm is incorporated fuzzy membership function into the LVQ(learning vector quantization) networks. Unlike the LVQ algorithm, this algorithm minimizes the network output errors which are the differences of clas s membership target and actual membership values, and results to minimize the distances between training patterns and competing neurons. Speaker Adaptation in speech synthesis is performed as follow;input speaker's codebook is mapped a reference speaker's codebook in fuzzy concepts. The Fuzzy VQ mapping replaces a codevector preserving its fuzzy membership function. The codevector correspondence histogram is obtained by accumulating the vector correspondence along the DTW optimal path. We use the Fuzzy VQ mapping to design a mapped codebook. The mapped codebook is defined as a linear combination of reference speaker's vectors using each fuzzy histogram as a weighting function with membership values. In adaptive-speech synthesis stage, input speech is fuzzy vector-quantized by the mapped codcbook, and then FCM arithmetic is used to synthesize speech adapted to input speaker. The speaker adaption experiments are carried out using speech of males in their thirties as input speaker's speech, and a female in her twenties as reference speaker's speech. Speeches used in experiments are sentences /anyoung hasim nika/ and /good morning/. As a results of experiments, we obtained a synthesized speech adapted to input speaker.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.267-271
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• 2007

본 논문은 원본이미지와 은닉이미지의 좋은 압축률과 만족할만한 이미지의 질, 그리고 외부공격에 강인한 이미지은닉의 한 방법으로 특이치 분해와 퍼지 군집화를 이용한 벡터양자화를 이용한 워터마킹 방법을 소개하였다. 실험에서는 은닉된 이미지의 비가시성과 외부공격에 대한 강인성을 증명하였다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.7
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• pp.1933-1942
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• 1998

분류 벡터 양자화(classified vector quantization: CVQ)〔2의 부코드북을 설계함에 있어서, 경쟁 학습 네트워크〔5〕-〔7〕 는 소속도의 이분법적 표현으로 상당한 소속도를 가지는 벡터들이 학습 과정에 무시되는 경향을 가진다. 이를 개선하기 위해 제안된 퍼지 경쟁 학습 네트워크〔8〕는 각 클러스터가 연속적인 소속도를 가진다는 개념을 도입하여 이와 같은 문제들을 해결했다. 그러나 퍼지 경쟁 학습 네트워크를 CVQ에 적용할 경우, 각 부코드북의 크기를 시행착오로 결정해야 하는 문제점을 여전히 가지고 있으며, 이러한 문제점들의 개선을 위하여 본 논문에서는 수정 퍼지 경쟁 학습 네트워크(modified fuzzy competitive learning network)를 제안한다. 수정 퍼지 경쟁 학습 네트워크는 퍼지 학습 네트워크가 가지는 이 분법적 소속도를 연속적인 소속도로 확장하여, 학습 과정중에 나타날 수 있는 지역 최소점 도달을 억제하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.4
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• pp.3-20
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• 1993

본 연구에서는 퍼지사상화(fuzzy mapping)에 의한 사상된(mapped) 코드북을 사용하는 화자적은 음성합성 알고리즘을 제안한다. 입력화자와 기준화자의 코드북은 신경망 클러스터링 알고리즘인 자율경쟁 학습을 사용하여 작성된다. 사상된 코드북은 입력 음성벡터에 대한 두 화자의 대응 코드벡터의 소속갑(membership value)으로 퍼지 히스토그랩을 작성하여 이들을 1차 결합함으로써 얻어지는 퍼지사상화에 의하여 작성된다. 음성합성시에는 사상된 코드북을 사용하여 입력화자의 음것을 퍼지 벡터양자화한 다음, CFM 연산으로 합성함으로써 입력화자에 적응된 합성음을 얻는다. 실험에서 여러 입력화자로 30대의 남성, 20대의 여성음을 사용하였고 기준음석으로 입력음성과는 다른 20대의 여성음성을 사용하였다.실험에 사용된 음성데이타는 문장/안녕하십니까/와/굿모닝/이다. 실험결과는 각각의 입력화자에 기준화자 음성이 적응된 합성음을 얻었다.

• The Journal of the Korea Contents Association
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• v.6 no.5
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• pp.20-28
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• 2006

This paper proposes visual-feature extraction for each band in wavelet domain with both spatial frequency features and multi resolution features, and the combination of visual features using fuzzy integral. In addition, it uses color feature expression method taking advantage of the frequency of the same color after color quantization for reducing quantization error, a disadvantage of the existing color histogram intersection method. Also, it is found that the final similarity can be represented in a linear combination of the respective factors(Homogram, color, energy) when each factor is independent one another. With respect to the combination patterns the fuzzy measurement is defined and the fuzzy integral is taken. Experiments are peformed on a database containing 1,000 color images. The proposed method gives better performance than the conventional method in both objective and subjective performance evaluation.