• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.33-38
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• 1999

In this paper, we combine a generalized analysis-by-synthesis (AbS) structure and an algebraic excitation scheme to propose a new 4kb/s speech codec. This codec partly uses the structure of G.729. We design a line spectrum pair (LSP) quantizer, an adaptive codebook, and an excitation codebook to fit the 4 kb/s bit rate. The codec has a 25㎳ algorithmic delay, which corresponds to a 20㎳ frame size and a 5㎳ lookahead. At the bit rates below 4kb/s, most CELP speech codecs using the AbS principle have a drawback that results a rapid degradation of speech quality. To overcome this drawback we use the generalized AbS structure which is efficient for the low bit rate speech codec. LP coefficients are converted to LSP and quantized using a predictive 2-stage VQ. A low complexity algebraic codebook which uses shifting method is used for the fixed codebook excitation, and gains of the adaptive codebook and the fixed codebook are quantized using the VQ. To evaluate the performance of the proposed codec A-B preference tests are done with the fixed rate 8kb/s QCELP. As the result of the test, the performance of the codec is similar to that of the fixed rate 8kb/s QCELP.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.4
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• pp.772-780
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• 1994

Vector quantization with two-channel conjugate codebook has been researched as an efficient coding technique that can reduce the computational complexity and codebook storage. This paper proposes FSVQ using two-channel conjugate codebook in order to reduce the number of state codebooks. Input vector in the two-channel conjugate FSVQ is coded with state codebook of a seperated state according to each codebook. In addition, LOT is adopted to obtain to obtain a high coding gain and to reduce blocking effect which appears in the block coding. As a result, although FSVQ can achieve higher data compression ratio than general vector quantization, it has a disadvantage of having a very large number of state codebooks. However FSVQ with two-channel conjugate codebooks can employ a significantly reduced number of state codebooks, even though it has a small loss in the PSNR compared with the conventional FSVQ using one codebook. Moreover FSVQ in the LOT domain can reduce blocking effect and high coding gain compared with FSVQ in the spatial domain.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2615-2628
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• 1997

In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.673-680
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• 2003

In this paper, we study the enhancement of VQ (Vector Quantization) design for text independent speaker recognition. In a concrete way, we present a non-iterative method which makes a vector quantization codebook and this method performs non-iterative learning so that the computational complexity is epochally reduced The proposed Classified Space VQ (CSVQ) design method for text Independent speaker recognition is generalized from Semi-noniterative VQ design method for text dependent speaker recognition. CSVQ contrasts with the existing desiEn method which uses the iterative learninE algorithm for every traininE speaker. The characteristics of a CSVQ design is as follows. First, the proposed method performs the non-iterative learning by using a Classified Space Codebook. Second, a quantization region of each speaker is equivalent for the quantization region of a Classified Space Codebook. And the quantization point of each speaker is the optimal point for the statistical distribution of each speaker in a quantization region of a Classified Space Codebook. Third, Classified Space Codebook (CSC) is constructed through Sample Vector Formation Method (CSVQ1, 2) and Hyper-Lattice Formation Method (CSVQ 3). In the numerical experiment, we use the 12th met-cepstrum feature vectors of 10 speakers and compare it with the existing method, changing the codebook size from 16 to 128 for each Classified Space Codebook. The recognition rate of the proposed method is 100% for CSVQ1, 2. It is equal to the recognition rate of the existing method. Therefore the proposed CSVQ design method is, reducing computational complexity and maintaining the recognition rate, new alternative proposal and CSVQ with CSC can be applied to a general purpose recognition.

• The KIPS Transactions:PartC
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• v.8C no.1
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• pp.105-112
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• 2001

In this paper, we present the advanced QCELP codebook search improving the qualification of speech, which can make QCELP vocoder used in noise robust system. While conventional QCELP usually searches stochastic codebook once, we can find that two times search is the most suitable for improving the quality of speech after we did 2-5 times search. Consequently, the advanced QCELP vocoder represents excitation signal in detail using two times precise quantization and so improve the qualification of speech. In our experiment, we use the speeches collected from circumstance (such as lecture room, house, street, laboratory etc.) without regarding noise as input dat and measure the speech Qualification using SNR, segSNR. As the result of the experiment, we find that the advanced QCELP makes SNR and segSNR improved by 38.35% and 65.51% respectively compared with conventional QCELP.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.877-886
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• 2005

Various frame recovery algorithms have been suggested to overcome the communication quality degradation problem due to Internet-typical impairments on Voice over IP(VoIP) communications. In this paper, we propose a new receiver-based recovery method which is able to enhance recovered speech quality with almost free computational cost and without an additional increment of delay and bandwidth consumption. Most conventional recovery algorithms try to recover the lost or erroneous speech frames by reconstructing missing coefficients or speech signal during speech decoding process. Thus they eventually need to modify the decoder software. The proposed frame recovery algorithm tries to reconstruct the missing frame itself, and does not require the computational burden of modifying the decoder. In the proposed scheme, the Vector Quantization(VQ) codebook indices of the erased frame are directly estimated by referring the pre-computed VQ Codebook Index Interpolation Tables(VCIIT) using the VQ indices from the adjacent(previous and next) frames. We applied the proposed scheme to the ITU-T G.723.1 speech coder and found that it improved reconstructed speech quality and outperforms conventional G.723.1 loss recovery algorithm. Moreover, the suggested simple scheme can be easily applicable to practical VoIP systems because it requires a very small amount of additional computational cost and memory space.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1411-1418
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• 1999

In this paper, we propose a fast motion estimation algorithm using motion prediction and neural network. Considering that the motion vectors have high spatial correlation, the motion vector of current block is predicted by those of neighboring blocks. The codebook of motion vector is designed by Kohonen self-organizing feature map(KSFM) learning algorithm which has a fast learning speed and 2-D adaptive chararteristics. Since the similar codevectors are closely located in the 2-D codebook the motion is progressively estimated from the predicted codevector in the codebook. Computer simulation results show that the proposed method has a good performance with reduced computational complexity.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.80-93
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• 1997

This paper proposes a new technique of optimal codebook design in multistage gain-shape vector quantization (MS-GS VQ) for wireless image communication. An original image is divided into a smany blocks as possible in order to get strong robustness to channel transmission errors: the original image is decomposed into a number of subband images, each of which contains a sperate spatial frequency information and is obtained by the biorthogonal wavlet transform; each subband is separated into several consecutive VQ stages, where each stage has a residual information of the previous stage; one vector in each stage is divided into two components-gain and shape. But, this decomposition genrates too many blocks and it thus makes the determination of optimal codebooks difficult. We overcome this difficulty by evolving each block's codebook independently with different genetic algorithm that uses each stage's individual training vectors. Th eimpact of th eproposed VQ technique on the channel transmission errors is compared with that of other VQ techniques. Simulation results show that the proposed VQ technique (MS-GS VQ) with the optimal codebook designe dy genetic algorithms is very robust to channel transmission errors even under the bursty and high BER conditions.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.1
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• pp.98-105
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• 2011

Reduced complexity codebook searching for Quantized Equal Gain Transmission(QEGT) is proposed over MIMO-OFDM systems. QEGT codebook is divided into M groups of Q index members. Each group has a representative index. At the 1st stage only the representative indices are searched then the best index is selected. At the 2nd stage the optimum index is determined only among the group of the selected representative index. This strategy reduces the overall index search algorithm comparing to the conventional methods. Monte-Carlo simulation shows that the searching complexity is reduced, but the link-level performance is still almost the same as the conventional methods when the number of transmission antennas are 3 to 7.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.5
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• pp.747-755
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• 1995

When codebooks designed by a clustering algorithm using training sets, a time-averaged distortion, which is called the inside-training-set- distortion (ITSD), is usually calculated in each iteration of the algorithm, since the input probability function is unknown in general. The algorithm stops if the ITSD no more significantly decreases. Then, in order to test the trained codebook, the outside-training-set-distortion (OTSD) is to be calculated by a time-averaged approximation using the test set. Hence codebooks that yield small values of the OTSD are regarded as good codebooks. In other words, the calculation of the OTSD is a criterion to testing a trained codebook. But, such an argument is not always true if some conditions are not satisfied. Moreover, in order to obtain an approximation of the OTSD using the test set, it is known that a large test set is requared in general. But, large test set causes heavy calculation com0plexity. In this paper, from the analyses in [16], it has been revealed that the enough size of the test set is only the same as that of the codebook when codebook size is large. Then a simple method to testing trained codebooks is addressed. Experimental results on synthetic data and real images supporting the analysis are also provided and discussed.