• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.91-97
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• 2013

Image and it's processing techniques are widely applied and very important in the recent IT environment. In this paper, we try to reconstruct original BMP(Bitmap) image into indexed image and codebook utilizing vector quantization and represent high quality image only with same pixel depth of previous indexed image like JPEG etc. That is, By adopting common map method onto index image with $2^n$ color codebook, image can be represented as high quality as $2^{n+1}$ color codebook. When proposed output image is compared with original BMP image, it provides as much around 2dB as higher PSNR than conventional 8 bit index image(normal JPEG). Furthermore, this improvement(2 dB higher PSNR) could be provided when using the 9 bit indexed image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2342-2348
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• 1999

DCT-based codebook design using binary tree was proposed to reduce computation time and to solve the initial codebook problem. In this method, DCT coefficient of training vectors that has maximum variance is to be a split key and the mean of coefficients at the location is used as split threshold, then balanced binary tree for final codebook is formed. However edge degradation appears in the reconstructed image, since the blocks of shade region are frequently selected for codevector. In this paper, we propose DCT-based vector quantization codebook design using unbalanced binary tree. Above all, the node that has the largest split key is splited. So the number of edge codevector can be increased. From the simulation results, this method reconstructs the edge region sincerely and shows higher PSNR than previous methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.21-28
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• 2016

We propose an adaptive scheme of a differential codebook for temporally correlated channels. And the codeword entries of the propose codebook are selected among the set of M-PSK constellations - the values of M proposed in this paper are 8, 16, or 32. Firstly, we analyze mathematically how the optimal spherical cap radius of the proposed codebook is tracked. Then, we explain the practical implementation of the proposed adaptive method. Practically, some candidate differential codebooks we propose in this paper can be switched according to the temporal correlation coefficients of wireless channels in the proposed scheme. Monte-Carlo simulations demonstrate that the achievable throughput performance employing the proposed codebook is always superior to those of the differential codebooks employing M-PSK constellations and non-adaptive differential codebooks with the same amount of feedback information.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4E
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• pp.123-127
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• 2005

In this paper, we propose a new method for reducing the number of distance calculations in the LBG (Linde, Buzo, Gray) algorithm, which is widely used method to construct a codebook in vector quantization of speech recognition system. The proposed algorithm can reduce the distance calculation between input vector and codeword by utilizing the observation that codewords are quickly stabilized as the number of iteration increases. From the simulation results, it is shown that we can reduce the running times over $43.77\%$ on average in comparison with current LBG algorithm without sacrificing the performance of codebook.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.115-118
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• 1999

One of the typical methods to design a codebook is K-means algorithm. This algorithm has the drawbacks that converges to a locally optimal codebook and its performance is mainly decided by an initial codebook. D. Lee's method is almost same as the K-means algorithm except for a modification of a distance value. Those methods have a fixed distance value during all iterations. After many iterations. because the distance between new codevectors and old codevectors is much shorter than the distance in the early stage of iterations, the new codevectors are not affected by distance value. But new codevectors decided in the early stage of learning iterations are much affected by distance value. Therefore it is not appropriate to fix the distance value during all iterations. In this paper, we propose a new algorithm using each different distance value between codevectors for a limited iterations in the early stage of learning iteration. In the experiment, the result show that the proposed method can design better codebooks than the conventional K-means algorithms.

• Phonetics and Speech Sciences
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• v.1 no.2
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• pp.3-8
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• 2009

In an effort to improve speech recognition, we investigated the effect of the number of clusters. In usual LBG clustering, the number of codebook clusters is doubled on each bifurcation and hence cannot be chosen arbitrarily in a natural way. To have the number of clusters at our control, we combined adaptive resonance theory (ART2) with LBG and perform the clustering in two stages. The codebook thus formed was used in subsequent processing of fuzzy vector quantization (FVQ) and HMM for speech recognition tests. Compared to conventional LBG, our method was shown to reduce the best recognition error rate by 0${\sim$}0.9% depending on the vocabulary size. The result also showed that between 400 and 800 would be the optimal number of clusters in the limit of small and large vocabulary speech recognitions of isolated words, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.102-109
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• 2001

In this paper, in order to reduce the computational complexity of codebook, we propose a fast search algorithm which takes advantage of the information generated in the process of the self-organizing map (SOM). In an attempt to demonstrate the influence of the ordering of codebook on the performance of the partial distance search (PDS), we present the results of computation savings for three cases of ordering of codebooks.

• ETRI Journal
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• v.27 no.2
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• pp.231-234
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• 2005

This letter proposes a new embedded speech coding structure based on the Adaptive Multi-Rate Wideband (AMR-WB) standard codec. The proposed coding scheme consists of three different bitrates where the two lower bitrates are embedded into the highest one. The embedded bitstream was achieved by modifying the algebraic codebook search procedure adopted for the AMR-WB codec. The proposed method provides the advantage of scalability due to the embedded bitstream, while it inevitably requires some additional computational complexity for obtaining two different code vectors of the higher bitrate modes. Compared to the AMR-WB codec, the embedded coder shows improved speech qualities for two higher bitrate modes with a slightly increased bitrate caused by the decreased coding efficiency of the algebraic codebook.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.109-112
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• 2003

In real time packetized voice applications, missing frames is a major source of voice quality degradation. Thus packet loss concealment(PLC) algorithms are needed to guarantee the QoS of the VoIP. Still current speech codecs for VoIP work poor when consecutive packet losses are issued. In this paper, we proposed a new PLC algorithm for the G.729 codec. Our algorithm works better especially when the consecutive packet loss occurs mainly because it adopts an adaptive gain controller utilizing the number of missing packet information combined with a fixed codebook vector estimation algorithm and LPC bandwidth expansion.

• Proceedings of the KSPS conference
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• 2005.04a
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• pp.87-90
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• 2005

Today's state-of the-art speech recognition systems typically use continuous distribution hidden Markov models with the mixtures of Gaussian distributions. To obtain higher recognition accuracy, the hidden Markov models typically require huge number of Gaussian distributions. Such speech recognition systems have problems that they require too much memory to run, and are too slow for large applications. Many approaches are proposed for the design of compact acoustic models. One of those models is subspace distribution clustering hidden Markov model. Subspace distribution clustering hidden Markov model can represent original full-space distributions as some combinations of a small number of subspace distribution codebooks. Therefore, how to make the codebook is an important issue in this approach. In this paper, we report some experimental results on various quantization methods to make more accurate models.