• Journal of IKEEE
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• v.17 no.3
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• pp.241-247
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• 2013

This paper presents the design of a System on Programmable Chip (SoPC) based on Field Programmable Gate Array (FPGA) for speech recognition in which Mel-Frequency Cepstral Coefficients (MFCC) for speech feature extraction and Vector Quantization for recognition are used. The implementing process of the speech recognition system undergoes the following steps: feature extraction, training codebook, recognition. In the first step of feature extraction, the input voice data will be transformed into spectral components and extracted to get the main features by using MFCC algorithm. In the recognition step, the obtained spectral features from the first step will be processed and compared with the trained components. The Vector Quantization (VQ) is applied in this step. In our experiment, Altera's DE2 board with Cyclone II FPGA is used to implement the recognition system which can recognize 64 words. The execution speed of the blocks in the speech recognition system is surveyed by calculating the number of clock cycles while executing each block. The recognition accuracies are also measured in different parameters of the system. These results in execution speed and recognition accuracy could help the designer to choose the best configurations in speech recognition on SoPC.

• The Journal of the Acoustical Society of Korea
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• v.8 no.5
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• pp.102-112
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• 1989

In this paper, we proposed the study on speaker-independent isolated word recognition for DDD area-name using vector quantization and chose total 146 DDD area-name to recognize words for application of dialing system. We made the codebook using 12th LPC cepstrum coefficients and used the minsum and the minimax method to find the centroid and we applied 3 splitting rule to a codebook generation. The single section and the multi section with time information were used to generate the codebooks and the over-lapped section codebook was used, too. From the experiment result, we proved that the minsum method was better than the minimax method and the evaluation of the system yielded an accuracy of about 90 percents In case of speaker-independent.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.54-57
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• 2000

In vector quantization (VQ), mean squared difference (MSD) is a widely used distance measure between vectors. But the distance between the means of each vector elements appears as a dominant quantity in MSD. In the case of image vectors, the coincidence of edge patterns is also important when the human visual system (HVS) is considered. Therefore, we propose a new distance measure that uses the variance of differences to encode vectors and to design codebooks. It can choose more proper codewords to reduce edge degradations and make a useful codebook, which has lots of various edge codewords in place of redundant shades.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.7-11
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• 2002

In this study, fur the shape-based image retrieval, a method using local differential invariants is proposed. This method calculates the differential invariant feature vector at every feature point extracted by Harris comer point detector. Then through vector quantization using LBG algorithm, all feature vectors are represented by a codebook index. All images are indexed by the histogram of codebook index, and by comparing the histograms the similarity between images is obtained. The proposed method is compared with the existing method by performing experiments for image database including various 1100 trademarks.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.448-455
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• 1996

In this paper, we have proposed a VQ algorithm which uses a generating order to make quantize feature vector of speech signal. The proposed algorithm inspects what codeword follows a(ter present codeword and adds new index to established codebook, when mapping speech signal. We present a variable bit rate for new codebook, and propose an efficient compressed way of information. In this way, the number of computation and the number of codewords to be searched are reduced considerably. The performance of the proposed VQ algorithm is evaluated by spectrum distortion measure and bit rate. The obtained spectrum distortion is reduced about 0.22 [db], and the bit rate is saved over 0.21 bit/frame.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.46-55
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• 1995

In this paper, we present a new wavelet transform-based CELP coder, called band selection wavelet transform CELP (BS-WTCELP) operated at 4.8 kbps. The proposed algorithm uses a band selection scheme of frequency bands of wavelet transform and selective vector quantization (VQ). The band selection and selective VQ structure is implemented by using a classified VQ structure. The proposed algorithm has about 0.5-1.0 dB improvement in segmental SNR compared with the conventional CELP that uses the random codebook search, while is has significantly reduced computational and storage complexity. Many experimental results have shown that the proposed algorithm is more suitable for most real-applications than the conventional CELP and wavelet transform CELP.

• 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 Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1307-1316
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• 1996

In this paper, we propose a vector quantization method which uses a dynamic address mapping based on exploring the high interblock correlation. In the proposed method, we reduce bit-rate by defining an address transform function, which maps a VQ address of an input block which will be encoded into a new address in the reordered codebook by using side match error. In one case that an original address can be transformed into a new transformed address which is lower than the threshold value, we encode the new address of the transformed convector, and in the other case we encode the address of the original convector which is not transformed. Experimental results indicate that the proposed scheme reduces the bit-rate by 45~50% compared with the ordi-nary VQ method forimage compression, at the same quality of the reconstructed image as that of the ordinary VQ system.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.31-34
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• 2000

In this paper, we proposed multispectral image compression method using CIP (classified inter-channel prediction) and SVQ (selective vector quantization) in wavelet domain. First, multispectral image is wavelet transformed and classified into one of three classes considering reflection characteristics of the subband with the lowest resolution. Then, for a reference channel which has the highest correlation with other channels, the variable VQ is performed in the classified intra-channel to remove spatial redundancy. For other channels, the CIP is performed to remove spectral redundancy. Finally, the prediction error is reduced by performing SVQ. Experiments are carried out on a multispectral image. The results show that the proposed method reduce the bit rate at higher reconstructed image quality and improve the compression efficiency compared to conventional method.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.979-982
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• 2002

Compressing image data by using Vector Quantization (VQ)［1］-［3］will compare Training Vectors with Codebook. The result is an index of position with minimum distortion. The implementing Random Codebook will reduce the image quality. This research presents the Splitting solution ［4］,［5］to implement the Codebook, which improves the image quality［6］by the average Training Vectors, then splits the average result to Codebook that has minimum distortion. The result from this presentation will give the better quality of the image than using Random Codebook.