• Title/Summary/Keyword: Model recognition

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A Study on the Implementation of Connected-Digit Recognition System and Changes of its Performance (연결 숫자음 인식 시스템의 구현과 성능 변화)

  • Yun Young-Sun;Park Yoon-Sang;Chae Yi-Geun
    • MALSORI
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    • no.45
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    • pp.47-61
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    • 2003
  • In this paper, we consider the implementation of connected digit recognition system and the several approaches to improve its performance. To implement efficiently the fixed or variable length digit recognition system, finite state network (FSN) is required. We merge the word network algorithm that implements the FSN with one pass dynamic programming search algorithm that is used for general speech recognition system for fast search. To find the efficient modeling of digit recognition system, we perform some experiments along the various conditions to affect the performance and summarize the results.

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Development of Non-Contacting Automatic Inspection Technology of Precise Parts (정밀부품의 비접촉 자동검사기술 개발)

  • Lee, Woo-Sung;Han, Sung-Hyun
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.6
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    • pp.110-116
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    • 2007
  • This paper presents a new technique to implement the real-time recognition for shapes and model number of parts based on an active vision approach. The main focus of this paper is to apply a technique of 3D object recognition for non-contacting inspection of the shape and the external form state of precision parts based on the pattern recognition. In the field of computer vision, there have been many kinds of object recognition approaches. And most of these approaches focus on a method of recognition using a given input image (passive vision). It is, however, hard to recognize an object from model objects that have similar aspects each other. Recently, it has been perceived that an active vision is one of hopeful approaches to realize a robust object recognition system. The performance is illustrated by experiment for several parts and models.

A Study on the Speech Recognition for Commands of Ticketing Machine using CHMM (CHMM을 이용한 발매기 명령어의 음성인식에 관한 연구)

  • Kim, Beom-Seung;Kim, Soon-Hyob
    • Journal of the Korean Society for Railway
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    • v.12 no.2
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    • pp.285-290
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    • 2009
  • This paper implemented a Speech Recognition System in order to recognize Commands of Ticketing Machine (314 station-names) at real-time using Continuous Hidden Markov Model. Used 39 MFCC at feature vectors and For the improvement of recognition rate composed 895 tied-state triphone models. System performance valuation result of the multi-speaker-dependent recognition rate and the multi-speaker-independent recognition rate is 99.24% and 98.02% respectively. In the noisy environment the recognition rate is 93.91%.

A Recognition System for Multi-Form Korean Characters Based on Hierarchical Temporal Memory

  • Haibao, Nan;Bae, Sun-Gap;Bae, Jong-Min;Kang, Hyun-Syug
    • Journal of Korea Multimedia Society
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    • v.12 no.12
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    • pp.1718-1727
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    • 2009
  • Traditional character recognition systems usually aim at characters with simple variation. With the development of multimedia technology, printed characters may appear more diversely. Existing recognition technologies can't deal with Hangul recognition effectively in diverse environments. This paper presents a recognition system for multi-form Korean characters called RSMFK, which is based on the model of Hierarchical Temporal Memory (HTM). Our system can effectively recognize the printed Korean characters of different fonts, scales, rotation, noise and background. HTM is a model which simulates the neocortex of human brain to recognize and memorize intelligently. Experimental results show that RSMFK performs a good recognition rate of 97.8% on average, which is proved to be obviously improved over the conventional methods.

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Object Recognition using Comparison of External Boundary

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • v.7 no.3
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    • pp.134-142
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    • 2019
  • As the 4th industry has been widely distributed, there is a need for a process of real-time image recognition in various fields such as identification of company employees, security maintenance, and development of military weapons. Therefore, in this paper, we will propose an algorithm that effectively recognizes a test object by comparing it with the DB model. The proposed object recognition system first expresses the outline of the test object as a set of vertices with the distances of predefined length or more. Then, the degree of matching of the structures of the two objects is calculated by examining the distances to the outline of the DB model from the vertices constituting the test object. Because the proposed recognition algorithm uses the outline of the object, the recognition process is easy to understand, simple to implement, and a satisfactory recognition result is obtained.

Design of Intelligent Emotion Recognition Model

  • Kim, Yi-gon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.7
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    • pp.611-614
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    • 2001
  • Voice is one of the most efficient communication media and it includes several kinds of factors about speaker, context emotion and so on. Human emotion is expressed is expressed in the speech, the gesture, the physiological phenomena(the breath, the beating of the pulse, etc). In this paper, the emotion recognition method model using neuro-fuzzy in order to have cognizance of emotion from voice signal is presented and simulated.

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Korean vowel recognition in noise using auditory model

  • Shim, Jae-Seong;Lee, Jae-Hyuk;Yoon, Tae-Sung;Beack, Seung-Hwa;Park, Sang-Hui
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10b
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    • pp.1037-1040
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    • 1988
  • In this study, we performed the recognition test on Korean vowel using peripheral auditory model. In addition, for the purpose of objective comparision, the recognition test is performed by extracting LPC cepstrum coefficients from the same data. And the same speech data are mixed with the Guaussian white noise quantitatively, then we repeated the same test, too. So we verified that this auditory model has a adaptability on noise.

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Improvement of Korean Sign Language Recognition System by User Adaptation (사용자 적응을 통한 한국 수화 인식 시스템의 개선)

  • Jung, Seong-Hoon;Park, Kwang-Hyun;Bien, Zeung-Nam
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.301-303
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    • 2007
  • This paper presents user adaptation methods to overcome limitations of a user-independent model and a user-dependent model in a Korean sign language recognition system. To adapt model parameters for unobserved states in hidden Markov models, we introduce new methods based on motion similarity and prediction from adaptation history so that we can achieve faster adaption and higher recognition rates comparing with previous methods.

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A Study on Discrete Hidden Markov Model for Vibration Monitoring and Diagnosis of Turbo Machinery (터보회전기기의 진동모니터링 및 진단을 위한 이산 은닉 마르코프 모델에 관한 연구)

  • Lee, Jong-Min;Hwang, Yo-ha;Song, Chang-Seop
    • The KSFM Journal of Fluid Machinery
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    • v.7 no.2 s.23
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    • pp.41-49
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    • 2004
  • Condition monitoring is very important in turbo machinery because single failure could cause critical damages to its plant. So, automatic fault recognition has been one of the main research topics in condition monitoring area. We have used a relatively new fault recognition method, Hidden Markov Model(HMM), for mechanical system. It has been widely used in speech recognition, however, its application to fault recognition of mechanical signal has been very limited despite its good potential. In this paper, discrete HMM(DHMM) was used to recognize the faults of rotor system to study its fault recognition ability. We set up a rotor kit under unbalance and oil whirl conditions and sampled vibration signals of two failure conditions. DHMMS of each failure condition were trained using sampled signals. Next, we changed the setup and the rotating speed of the rotor kit. We sampled vibration signals and each DHMM was applied to these sampled data. It was found that DHMMs trained by data of one rotating speed have shown good fault recognition ability in spite of lack of training data, but DHMMs trained by data of four different rotating speeds have shown better robustness.

Online Recognition of Handwritten Korean and English Characters

  • Ma, Ming;Park, Dong-Won;Kim, Soo Kyun;An, Syungog
    • Journal of Information Processing Systems
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    • v.8 no.4
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    • pp.653-668
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    • 2012
  • In this study, an improved HMM based recognition model is proposed for online English and Korean handwritten characters. The pattern elements of the handwriting model are sub character strokes and ligatures. To deal with the problem of handwriting style variations, a modified Hierarchical Clustering approach is introduced to partition different writing styles into several classes. For each of the English letters and each primitive grapheme in Korean characters, one HMM that models the temporal and spatial variability of the handwriting is constructed based on each class. Then the HMMs of Korean graphemes are concatenated to form the Korean character models. The recognition of handwritten characters is implemented by a modified level building algorithm, which incorporates the Korean character combination rules within the efficient network search procedure. Due to the limitation of the HMM based method, a post-processing procedure that takes the global and structural features into account is proposed. Experiments showed that the proposed recognition system achieved a high writer independent recognition rate on unconstrained samples of both English and Korean characters. The comparison with other schemes of HMM-based recognition was also performed to evaluate the system.