• 제목/요약/키워드: markov models

검색결과 490건 처리시간 0.024초

2층 구조의 입체 시각형 신경망 기반 음소인식 (Phoneme Recognition based on Two-Layered Stereo Vision Neural Network)

  • Kim, Sung-Ill;Kim, Nag-Cheol
    • 한국멀티미디어학회논문지
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    • 제5권5호
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    • pp.523-529
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    • 2002
  • 본 연구는 입체 시각을 위한 신경망에 대한 연구 결과로서 인간의 음성을 인식하는데 적용된다. 입체 시각신경망(SVNN)에 기반한 음성인식에서, 먼저 입력된 음성 신호를 표준 모델과 비교함으로써 유사성이 얻어진다. 이 값들은 다이나믹한 처리 과정으로 주어지고 이웃한 신경소자들 사이에서 경쟁적이고 협력적인 처리를 거치게 된다. 이러한 다이나믹한 처리과정을 통해 단 하나의 가장 우수한 신경세포(winner neuron)만이 최후에 검출된다. 비교연구에서 2층 구조의 SVNN은 HMM 인식기보다 인식정확도 측면에서 7.7% 더 높았다. 평가 결과. SVNN은 기손리 HMM 인식기 성능을 능가하는 것으로 나타났다.

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연속 음성에서의 신경회로망을 이용한 화자 적응 (Speaker Adaptation Using Neural Network in Continuous Speech Recognition)

  • 김선일
    • 한국음향학회지
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    • 제19권1호
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    • pp.11-15
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    • 2000
  • RM 음성 Corpus를 이용한 화자 적응 연속 음성 인식을 수행하였다. RM Corpus의 훈련용 데이터를 이용해서 기준화자에 대한 HMM 학습을 실시하고 평가용 데이터를 이용하여 화자 적응 인식에 대한 평가를 실시하였다. 화자 적응을 위해서는 훈련용 데이터의 일부가 사용되었다. DTW를 이용하여 인식 대상화자의 데이터를 기준화자의 데이터와 시간적으로 일치시키고 오차 역전파 신경회로망을 사용하여 인식 대상화자의 스펙트럼이 기준화자의 스펙트럼 특성을 지니도록 변환시켰다. 최적의 화자 적응이 이루어지도록 하기 위해 신경회로망의 여러 요소들을 변화시키면서 실험을 실시하고 그 결과를 제시하였다. 학습을 거쳐 적절한 가중치를 지닌 신경회로망을 이용하여 기준화자에 적응시킨 결과 단어 인식율이 최대 2.1배, 단어 정인식율이 최대 4.7배 증가하였다.

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이산 HM을 이용한 실시간 음성인식 다이얼링 시스템 개발 (Development of a Read-time Voice Dialing System Using Discrete Hidden Markov Models)

  • 이세웅;최승호;이미숙;김홍국;오광철;김기철;이황수
    • The Journal of the Acoustical Society of Korea
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    • 제13권1E호
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    • pp.89-95
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    • 1994
  • 본 논문에서는 화자독립으로 100단어를 인식할 수 있는 실시간 음성인식 다이얼링 시스템의 개발에 대하여 기술하였다. 이 시스템에서 음성인식 알고리즘은 전화선 인터페이스를 갖춘 DSP 보드상에 구현되었으며, IBM PC AT/486 상에서 작동된다. DSP 보드에서는 단어의 시작점이 검출된 후에 특징추출, 벡터양자화 그리고 끝점검출 과정이 실시간으로 10 msec의 프레임 구간마다 수행된다. 또한, 본 시스템에서는 인식시간과 기억용량을 줄이기 위해 VQ 코드북의 크기와 끝점검출 과정을 최적화하였다. 본 실시간 음성인식 다이얼링 시스템은 데모 시스템으로 구현되어 대전엑스포‘93에서 한국이동통신의 MOBILAB 내에 전시되었다.

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신규호에 대한 지체가 허용된 셀룰라 이동통신시스템에서 최적 호제어 연구 (Optimal Call Control Strategies in a Cellular Mobile Communication System with a Buffer for New Calls)

  • Paik, Chun-hyun;Chung, Yong-joo;Cha, Dong-wan
    • 한국경영과학회지
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    • 제23권3호
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    • pp.135-151
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    • 1998
  • The demand of large capacity in coming cellular systems makes inevitable the deployment of small cells, rendering more frequent handoff occurrences of calls than in the conventional system. The key issue is then how effectively to reduce the chance of unsuccessful handoffs, since the handoff failure is less desirable than that of a new call attempt. In this study, we consider the control policies which give priority to handoff calls by limiting channel assignment for the originating new calls, and allow queueing the new calls which are rejected at their first attempts. On this system. we propose the problem of finding an optimal call control strategy which optimizes the objective function value, while satisfying the requirements on the handoff/new call blocking probabilities and the new call delay. The objective function takes the most general form to include such well-known performance measures as the weighted average carried traffic and the handoff call blocking probability. The problem is formulated into two different linear programming (LP) models. One is based on the direct employment of steady state equations, and the other uses the theory of semi-Markov decision process. Two LP formulations are competitive each other, having its own strength in the numbers of variables and constraints. Extensive experiments are also conducted to show which call control strategy is optimal under various system environments having different objective functions and traffic patterns.

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Speaker-Dependent Emotion Recognition For Audio Document Indexing

  • Hung LE Xuan;QUENOT Georges;CASTELLI Eric
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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    • pp.92-96
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    • 2004
  • The researches of the emotions are currently great interest in speech processing as well as in human-machine interaction domain. In the recent years, more and more of researches relating to emotion synthesis or emotion recognition are developed for the different purposes. Each approach uses its methods and its various parameters measured on the speech signal. In this paper, we proposed using a short-time parameter: MFCC coefficients (Mel­Frequency Cepstrum Coefficients) and a simple but efficient classifying method: Vector Quantification (VQ) for speaker-dependent emotion recognition. Many other features: energy, pitch, zero crossing, phonetic rate, LPC... and their derivatives are also tested and combined with MFCC coefficients in order to find the best combination. The other models: GMM and HMM (Discrete and Continuous Hidden Markov Model) are studied as well in the hope that the usage of continuous distribution and the temporal behaviour of this set of features will improve the quality of emotion recognition. The maximum accuracy recognizing five different emotions exceeds $88\%$ by using only MFCC coefficients with VQ model. This is a simple but efficient approach, the result is even much better than those obtained with the same database in human evaluation by listening and judging without returning permission nor comparison between sentences [8]; And this result is positively comparable with the other approaches.

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Hand Gesture Recognition using Optical Flow Field Segmentation and Boundary Complexity Comparison based on Hidden Markov Models

  • Park, Sang-Yun;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제14권4호
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    • pp.504-516
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    • 2011
  • In this paper, we will present a method to detect human hand and recognize hand gesture. For detecting the hand region, we use the feature of human skin color and hand feature (with boundary complexity) to detect the hand region from the input image; and use algorithm of optical flow to track the hand movement. Hand gesture recognition is composed of two parts: 1. Posture recognition and 2. Motion recognition, for describing the hand posture feature, we employ the Fourier descriptor method because it's rotation invariant. And we employ PCA method to extract the feature among gesture frames sequences. The HMM method will finally be used to recognize these feature to make a final decision of a hand gesture. Through the experiment, we can see that our proposed method can achieve 99% recognition rate at environment with simple background and no face region together, and reduce to 89.5% at the environment with complex background and with face region. These results can illustrate that the proposed algorithm can be applied as a production.

CONTINUOUS DIGIT RECOGNITION FOR A REAL-TIME VOICE DIALING SYSTEM USING DISCRETE HIDDEN MARKOV MODELS

  • Choi, S.H.;Hong, H.J.;Lee, S.W.;Kim, H.K.;Oh, K.C.;Kim, K.C.;Lee, H.S.
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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    • pp.1027-1032
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    • 1994
  • This paper introduces a interword modeling and a Viterbi search method for continuous speech recognition. We also describe a development of a real-time voice dialing system which can recognize around one hundred words and continuous digits in speaker independent mode. For continuous digit recognition, between-word units have been proposed to provide a more precise representation of word junctures. The best path in HMM is found by the Viterbi search algorithm, from which digit sequences are recognized. The simulation results show that a interword modeling using the context-dependent between-word units provide better recognition rates than a pause modeling using the context-independent pause unit. The voice dialing system is implemented on a DSP board with a telephone interface plugged in an IBM PC AT/486.

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베이지안 방법을 이용한 정상성 및 비정상성 GEV모형의 불확실성 비교 연구 (Comparison Study of Uncertainty between Stationary and Nonstationary GEV Models using the Bayesian Inference)

  • 김한빈;주경원;정영훈;허준행
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2016년도 학술발표회
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    • pp.298-298
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    • 2016
  • 최근 기후변화의 영향으로 시간에 따라 자료 및 통계적 특성이 변하는 비정상성이 다양한 수문자료에서 관측됨에 따라 비정상성 빈도해석에 대한 연구가 활발히 진행되고 있다. 비정상성 빈도해석에 사용되는 비정상성 확률 모형은 기존의 매개변수를 시간에 따라 변하는 공변량이 포함된 함수의 형태로 나타내기 때문에, 정상성 확률 모형에 비해 매개변수의 개수가 많으며 복잡한 형태를 가지게 된다. 따라서 본 연구에서는 비정상성 고려 시 모형이 복잡해짐에 따라 매개변수 및 확률 수문량의 불확실성이 어떻게 변하는지 알아보고자 하였다. 베이지안 방법은 매개변수 추정 및 확률 수문량의 산정 뿐 아니라 이에 대한 불확실성을 정량화할 수 있는 방법 중 하나이다. 따라서 베이지안 방법에서 매개변수 추정에 주로 쓰이는 Monte Carlo Markov Chain (MCMC) 방법 중 하나인 Metropolis-Hastings 알고리즘을 이용하여 정상성 및 비정상성 GEV모형에 대한 매개변수 및 확률수문량의 사후분포를 산정하였다. 산정된 사후분포의 사후구간을 통해 각 모형의 불확실성을 정량화하였으며, 계산된 불확실성의 비교를 통해 모형의 복잡성이 불확실성에 미치는 영향을 평가하였다.

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Seismic risk assessment of intake tower in Korea using updated fragility by Bayesian inference

  • Alam, Jahangir;Kim, Dookie;Choi, Byounghan
    • Structural Engineering and Mechanics
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    • 제69권3호
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    • pp.317-326
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    • 2019
  • This research aims to assess the tight seismic risk curve of the intake tower at Geumgwang reservoir by considering the recorded historical earthquake data in the Korean Peninsula. The seismic fragility, a significant part of risk assessment, is updated by using Bayesian inference to consider the uncertainties and computational efficiency. The reservoir is one of the largest reservoirs in Korea for the supply of agricultural water. The intake tower controls the release of water from the reservoir. The seismic risk assessment of the intake tower plays an important role in the risk management of the reservoir. Site-specific seismic hazard is computed based on the four different seismic source maps of Korea. Probabilistic Seismic Hazard Analysis (PSHA) method is used to estimate the annual exceedance rate of hazard for corresponding Peak Ground Acceleration (PGA). Hazard deaggregation is shown at two customary hazard levels. Multiple dynamic analyses and a nonlinear static pushover analysis are performed for deriving fragility parameters. Thereafter, Bayesian inference with Markov Chain Monte Carlo (MCMC) is used to update the fragility parameters by integrating the results of the analyses. This study proves to reduce the uncertainties associated with fragility and risk curve, and to increase significant statistical and computational efficiency. The range of seismic risk curve of the intake tower is extracted for the reservoir site by considering four different source models and updated fragility function, which can be effectively used for the risk management and mitigation of reservoir.

A Maximum A Posterior Probability based Multiuser Detection Method in Space based Constellation Network

  • Kenan, Zhang;Xingqian, Li;Kai, Ding;Li, Li
    • International Journal of Computer Science & Network Security
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    • 제22권12호
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    • pp.51-56
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    • 2022
  • In space based constellation network, users are allowed to enter or leave the network arbitrarily. Hence, the number, identities and transmitted data of active users vary with time and have considerable impacts on the receiver's performance. The so-called problem of multiuser detection means identifying the identity of each active user and detecting the data transmitted by each active user. Traditional methods assume that the number of active users is equal to the maximum number of users that the network can hold. The model of traditional methods are simple and the performance are suboptimal. In this paper a Maximum A Posteriori Probability (MAP) based multiuser detection method is proposed. The proposed method models the activity state of users as Markov chain and transforms multiuser detection into searching optimal path in grid map with BCJR algorithm. Simulation results indicate that the proposed method obtains 2.6dB and 1dB Eb/N0 gains respectively when activity detection error rate and symbol error rate reach 10-3, comparing with reference methods.