• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.8-14
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• 2009

A Hidden Markov Model(HMM)-based information extraction method is proposed in this paper. The proposed extraction method is applied to extraction of products' prices. The input of the proposed IESHMM is the URLs of a search engine's interface, which contains the names of the product types. The output of the system is the list of extracted slots of each product: name, price, image, and URL. With the observation data set Maximum Likelihood algorithm and Baum-Welch algorithm are used for the training of HMM and The Viterbi algorithm is then applied to find the state sequence of the maximal probability that matches the observation block sequence. When applied to practical problems, the proposed HMM-based system shows improved results over a conventional method, PEWEB, in terms of recall ration and accuracy.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.149-157
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• 2011

In this paper, we propose a new cardiac disorder classification method using an support vector machine (SVM) to combine hidden Markov model (HMM) and murmur existence information. Using cepstral features and the HMM Viterbi algorithm, we segment input heart sound signals into HMM states for each cardiac disorder model and compute log-likelihood (score) for every state in the model. To exploit the temporal position characteristics of murmur signals, we divide the input signals into two subbands and compute murmur probability of every subband of each frame, and obtain the murmur score for each state by using the state segmentation information obtained from the Viterbi algorithm. With an input vector containing the HMM state scores and the murmur scores for all cardiac disorder models, SVM finally decides the cardiac disorder category. In cardiac disorder classification experimental results, the proposed method shows the relatively improvement rate of 20.4 % compared to the HMM-based classifier with the conventional cepstral features.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.85-94
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• 2017

In this paper, I proposed a sound model generation and a most frequent model search algorithm for recognizing animal vocalization. The sound model generation algorithm generates a optimal set of models through repeating processes such as the training process, the Viterbi Search process, and the most frequent model search process while adjusting HMM(Hidden Markov Model) structure to improve global recognition rate. The most frequent model search algorithm searches the list of models produced by Viterbi Search Algorithm for the most frequent model and makes it be the final decision of recognition process. It is implemented using MFCC(Mel Frequency Cepstral Coefficient) for the sound feature, HMM for the model, and C# programming language. To evaluate the algorithm, a set of animal sounds for 27 species were prepared and the experiment showed that the sound model generation algorithm generates 27 HMM models with 97.29 percent of recognition rate.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.66-75
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• 2002

For the theoretical performance analysis of Viterbi Decoder for wireless LAN with data rate 12Mbps, code rate 1/2 and constraint length 7 defined in IEEE 802.11a, the transfer function is derived using Cramer's rule and the first-event error probability and bit error probability is derived under the AWGN. In the design process, input symbol is quantized into 16 steps for 4 bit soft decision and register exchange method instead of memory method is proposed for trace back, which enables the majority at the final decision stage. In the implementation, the Viterbi decoder based on parallel architecture with pipelined scheme for processing 12Mbps high speed data rate and AWGN generator are implemented using FPGA chips. And then its performance is verified in real time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.984-995
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• 1996

Data errors according to the various noises caused in the satellite communication links are corrected by the Viterbi decoding algorithm which has extreme error correcting capability. In this paper, we designed and implemented a convolutional encoder and Viterbi decoder ASIC which is used to encode the input data at the transmit side and correct the errors of the received data at the receive side for use in the VSAT communication system. And this chip may be used in any BPSK, QPSK, or OQPSK transmission system. The ambiguity resolver corrects PSK modem ambiguities by delaying, interting, and/or exchanging code symbol to restore their original sequence and polarity. In case of previous decoding system, ambiguity state(AS) of data is resolved by external control logic and extra redundancy data are needed to resolve AS. But, by adopting decoder proposed in this paper, As of data is resolved automatically by internal logic of decoder in case of continuous mode, and by external As line withoug extra redudancy data in burst mode case. So, decoding parts are simple in continuous mode and transmission efficiency is increased in bust mode. The features of this chip are full duplex operation with independent transmit and receive control and clocks, start/stop inputs for use in burst mode systems, loopback function to verify encoder and decoder, and internal or external control to resolve ambinguity state. For verification of the function and performance of a fabricated ASIC chip, we equiped this chip in the Central and Remote Earth Station of VSAT system, and did the performance test using the commerical INTELSAT VII under the real satellite link environmens. The results of test were demonstrated the superiority of performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.891-897
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• 2003

Partial response maxim likelihood (PRML) is a powerful and indispensable detection scheme for perpendicular magnetic recording channels. The performance of PRML can be improved by incorporating a noise prediction scheme into branch metric computations of Viterbi algorithm (VA). However, the systems constructed by VA have shortcomings in the form of high complexity and cost. In this connection, a new simple detection scheme is proposed by exploiting the minimum run-length parameter d=1 of RLL code. The proposed detection scheme have a slicer instead of Viterbi detector and a noise predictor as a feedback filter. Therefore, to improve BER performance, the proposed detection scheme is extended to dual detection scheme for improving the BER performance. Simulation results show that the proposed scheme has a comparable performance to noise-predictive maximum likelihood (NPML) detector with less complexity when the partial response (PR) target is (1,2,1).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.5C
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• pp.411-421
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• 2002

In this paper, we present a new survivor path memory management method and a dedicated hardware architecture for the design of high-speed Viterbi decoders in modern digital communication systems. In the proposed method, a novel use of k-starting node number deciding circuits enables to acheive the immediate traceback of the merged survivor path from which we can decode output bits, and results in smaller survivor path memory size and processing delay time than the previously known methods. Also, in the proposed method, the survivor path memory can be constructed with ease using a simple standard dual-ported memory since one read-pointer and one write-pointer, that are updated at the same rate, are required for managing the survivor path: the previously known algorithms require either complex k-ported memory structure or k-times faster read capability than write. With a moderate hardware cost for immediate traceback capability the proposed method is superior to the previously known methods for high-speed Viterbi decoding.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1E
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• pp.11-19
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• 1994

Hidden Markov Models (HMM's) with explicit state duration density (HMM/SD) can represent the time-varying characteristics of speech signals more accurately. However, such an advantage is reduced in relatively smooth state duration densities or ling bounded duration. To solve this problem, we propose HMM's with global path constraint (HMM/GPC) where the transition between states occur only within prescribed time slots. HMM/GPC explicitly limits state durations and accurately describes the temproal structure of speech simply and efficiently. HMM's formed by combining HMM/GPC with HMM/SD are also presented (HMM/SD+GPC) and performances are compared. HMM/GPC can be implemented with slight modifications to the conventional Viterbi algorithm. HMM/GPC and HMM/SD_GPC not only show superior performance than the conventional HMM and HMM/SD but also require much less computation. In the speaket independent isolated word recognition experiments, the minimum recognition eror rate of HMM/GPC(1.6%) is 1.1% lower than the conventional HMM's and the required computation decreased about 57%.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.311-318
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• 2013

This paper deals with a noise reduction algorithm which uses the binary masking in the time-frequency domain. To improve speech intelligibility in noise, noise-masked speech is decomposed into time-frequency units and mask "0" is assigned to masker-dominant region removing time-frequency units where noise is dominant compared to speech. In the previous research, Gaussian mixture models were used to classify the speech-dominant region and noise-dominant region which correspond to mask "1" and mask "0", respectively. In each frequency band, data were collected and trained to build the Gaussian mixture models and detection procedure is performed to the test data where each time-frequency unit belongs to speech-dominant region or noise-dominant region. In this paper, we consider the correlation of masks in the frequency domain and propose a post-processing method which exploits the Viterbi algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.53-57
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• 2002

Recently, digital communication system becomes high speed, as communication demand dose not only increases sharply, but an image, voice various kinds data also comes multimedia. In transmitting data at a high speed, the main problem is fading by multipath. A linear or nonlinear distortion arise In multipath channel fading from ISI(Intersymbol Interference). For restoring this distorted signal, A lot of equalizer and adaptive algorithm is introduced. This paper compares and analysises, for improving communication quality in channel which is long delay spread, performance of decision feedback equalizer by RLS algorithm, a channel estimation by RLS-MLSE and viterbi equalizer Particularly, there Is exactly channel estimation of impluse response and excellent property of equalization about channel, which delay spread is long impluse response comparatively and is property of non-minimun phase.