• Title, Summary, Keyword: recognition

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The Study on Korean Phoneme for Korean Speech Recogintion

  • Hwang, Young-Soo
    • Proceedings of the IEEK Conference
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    • pp.629-632
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    • 2000
  • In this paper, we studied on the phoneme classification for Korean speech recognition. In the case of making large vocabulary speech recognition system, it is better to use phoneme than syllable or word as recognition unit. And, In order to study the difference of speech recognition according to the number of phoneme as recognition unit, we used the speech toolkit of OGI in U.S.A as recognition system. The result showed that the performance of diphthong being unified was better than that of seperated diphthongs, and we required the better result when we used the biphone than when using mono-phone as recognition unit.

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A Hybrid SVM-HMM Method for Handwritten Numeral Recognition

  • Kim, Eui-Chan;Kim, Sang-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • pp.1032-1035
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    • 2003
  • The field of handwriting recognition has been researched for many years. A hybrid classifier has been proven to be able to increase the recognition rate compared with a single classifier. In this paper, we combine support vector machine (SVM) and hidden Markov model (HMM) for offline handwritten numeral recognition. To improve the performance, we extract features adapted for each classifier and propose the modified SVM decision structure. The experimental results show that the proposed method can achieve improved recognition rate for handwritten numeral recognition.

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The small scale Voice Dialing System using TMS320C30 (TMS320C30을 이용한 소규모 Voice Dialing 시스템)

  • 이항섭
    • Proceedings of the Acoustical Society of Korea Conference
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    • pp.58-63
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    • 1991
  • This paper describes development of small scale voice dialing system using TMS320C30. Recognition vocabuliary is used 50 department name within university. In vocabulary below the middle scale, word unit recognition is more practice than phoneme unit or syllable unit recognition. In this paper, we performend recognition and model generation using DMS(Dynamic Multi-Section) and implemeted voice dialing system using TMS320C30. As a result of recognition, we achieved a 98% recognition rate in condition of section 22 and weight 0.6 and recognition time took 4 seconds.

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A Study On Text Independent Speaker Recognition Using Eigenspace (고유영역을 이용한 문자독립형 화자인식에 관한 연구)

  • 함철배;이동규;이두수
    • Proceedings of the IEEK Conference
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    • pp.671-674
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    • 1999
  • We report the new method for speaker recognition. Until now, many researchers have used HMM (Hidden Markov Model) with cepstral coefficient or neural network for speaker recognition. Here, we introduce the method of speaker recognition using eigenspace. This method can reduce the training and recognition time of speaker recognition system. In proposed method, we use the low rank model of the speech eigenspace. In experiment, we obtain good recognition result.

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Face Recognition of partial faces using LDA (LDA를 이용한 부분 얼굴 인식)

  • Park, Lee-Ju;On, Seung-Yeop
    • Proceedings of the KIEE Conference
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    • pp.1006-1009
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    • 2003
  • In this paper, we propose a technique of the recognition of partial face. Most of the research is concentrated on the recognition of whole face Since part of the face area in an image can be damaged or overlapped, face recognition based on partial face is required. PCA and LDA technique is applied to the recognition of partial face. Also, a new method to combine the results of the recognition of parts of the face.

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Pattern Recognition Methods for Emotion Recognition with speech signal

  • Park Chang-Hyun;Sim Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.2
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    • pp.150-154
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    • 2006
  • In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.

A Real-Time Implementation of Speech Recognition System Using Oak DSP core in the Car Noise Environment (자동차 환경에서 Oak DSP 코어 기반 음성 인식 시스템 실시간 구현)

  • Woo, K.H.;Yang, T.Y.;Lee, C.;Youn, D.H.;Cha, I.H.
    • Speech Sciences
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    • v.6
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    • pp.219-233
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    • 1999
  • This paper presents a real-time implementation of a speaker independent speech recognition system based on a discrete hidden markov model(DHMM). This system is developed for a car navigation system to design on-chip VLSI system of speech recognition which is used by fixed point Oak DSP core of DSP GROUP LTD. We analyze recognition procedure with C language to implement fixed point real-time algorithms. Based on the analyses, we improve the algorithms which are possible to operate in real-time, and can verify the recognition result at the same time as speech ends, by processing all recognition routines within a frame. A car noise is the colored noise concentrated heavily on the low frequency segment under 400 Hz. For the noise robust processing, the high pass filtering and the liftering on the distance measure of feature vectors are applied to the recognition system. Recognition experiments on the twelve isolated command words were performed. The recognition rates of the baseline recognizer were 98.68% in a stopping situation and 80.7% in a running situation. Using the noise processing methods, the recognition rates were enhanced to 89.04% in a running situation.

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A Study on the Recognition of Face Based on CNN Algorithms (CNN 알고리즘을 기반한 얼굴인식에 관한 연구)

  • Son, Da-Yeon;Lee, Kwang-Keun
    • Korea Journal of Artificial Intelligence
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    • v.5 no.2
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    • pp.15-25
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    • 2017
  • Recently, technologies are being developed to recognize and authenticate users using bioinformatics to solve information security issues. Biometric information includes face, fingerprint, iris, voice, and vein. Among them, face recognition technology occupies a large part. Face recognition technology is applied in various fields. For example, it can be used for identity verification, such as a personal identification card, passport, credit card, security system, and personnel data. In addition, it can be used for security, including crime suspect search, unsafe zone monitoring, vehicle tracking crime.In this thesis, we conducted a study to recognize faces by detecting the areas of the face through a computer webcam. The purpose of this study was to contribute to the improvement in the accuracy of Recognition of Face Based on CNN Algorithms. For this purpose, We used data files provided by github to build a face recognition model. We also created data using CNN algorithms, which are widely used for image recognition. Various photos were learned by CNN algorithm. The study found that the accuracy of face recognition based on CNN algorithms was 77%. Based on the results of the study, We carried out recognition of the face according to the distance. Research findings may be useful if face recognition is required in a variety of situations. Research based on this study is also expected to improve the accuracy of face recognition.

Recognition Time Reduction Technique for the Time-synchronous Viterbi Beam Search (시간 동기 비터비 빔 탐색을 위한 인식 시간 감축법)

  • 이강성
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.6
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    • pp.46-50
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    • 2001
  • This paper proposes a new recognition time reduction algorithm Score-Cache technique, which is applicable to the HMM-base speech recognition system. Score-Cache is a very unique technique that has no other performance degradation and still reduces a lot of search time. Other search reduction techniques have trade-offs with the recognition rate. This technique can be applied to the continuous speech recognition system as well as the isolated word speech recognition system. W9 can get high degree of recognition time reduction by only replacing the score calculating function, not changing my architecture of the system. This technique also can be used with other recognition time reduction algorithms which give more time reduction. We could get 54% of time reduction at best.

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Recognition Performance Improvement of Unsupervised Limabeam Algorithm using Post Filtering Technique

  • Nguyen, Dinh Cuong;Choi, Suk-Nam;Chung, Hyun-Yeol
    • IEMEK Journal of Embedded Systems and Applications
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    • v.8 no.4
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    • pp.185-194
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    • 2013
  • Abstract- In distant-talking environments, speech recognition performance degrades significantly due to noise and reverberation. Recent work of Michael L. Selzer shows that in microphone array speech recognition, the word error rate can be significantly reduced by adapting the beamformer weights to generate a sequence of features which maximizes the likelihood of the correct hypothesis. In this approach, called Likelihood Maximizing Beamforming algorithm (Limabeam), one of the method to implement this Limabeam is an UnSupervised Limabeam(USL) that can improve recognition performance in any situation of environment. From our investigation for this USL, we could see that because the performance of optimization depends strongly on the transcription output of the first recognition step, the output become unstable and this may lead lower performance. In order to improve recognition performance of USL, some post-filter techniques can be employed to obtain more correct transcription output of the first step. In this work, as a post-filtering technique for first recognition step of USL, we propose to add a Wiener-Filter combined with Feature Weighted Malahanobis Distance to improve recognition performance. We also suggest an alternative way to implement Limabeam algorithm for Hidden Markov Network (HM-Net) speech recognizer for efficient implementation. Speech recognition experiments performed in real distant-talking environment confirm the efficacy of Limabeam algorithm in HM-Net speech recognition system and also confirm the improved performance by the proposed method.