• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.13-20
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• 2005

In this paper, I recognized Korean isolated words using CVEM which is suggested by M. Bilginer et al. CVEM is an algorithm which is easy to extract the common properties from training voice signals and also doesn't need complex calculation. In addition CVEM shows high accuracy in recognition results. But, CVEM has couple of problems which are impossible to use for many training voices and no discriminant information among extracted common vectors. To get the optimal common vectors from certain voice classes, various voices should be used for training. But CVEM is impossible to get continuous high accuracy in recognition because CVEM has a limitation to use many training voices and the absence of discriminant information among common vectors can be the source of critical errors. To solve above problems and improve recognition rate, k-clustering subspace method and DCVEM suggested. And did various experiments using voice signal database made by ETRI to prove the validity of suggested methods. The result of experiments shows improvements in performance. And with proposed methods, all the CVEM problems can be solved with out calculation problem.

• Annual Conference of KIPS
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• 2022.11a
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• pp.977-979
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• 2022

본 논문에서는 시중에서 판매되는 점자학습 기기의 단점들을 보완한 점자학습 보드를 제안한다. 학습 보드는 다음과 같은 기능을 수행한다. 첫째, 자음, 모음 등의 기초적인 글자 학습, 단어와 문장 학습, 게임학습, 총 세 가지의 학습 모드를 지원하는 기능. 둘째, 사용자의 학습 데이터를 분석하여 마지막 학습 일자, 학습 진행 상황 등의 다양한 요소를 고려한 학습, 복습 내용을 자동으로 업로드하는 기능. 셋째, 기기에 연동된 애플리케이션을 통해 학습상태를 확인하고 기기를 조작하는 기능. 넷째, 학습 보드와 앱의 음성안내, 생체인식을 사용한 로그인, 음성인식을 통한 언어 변환, 보드 자동 교체 등의 사용자 편의성을 위한 기능이다. 본 논문은 이를 통해 점자학습에 대한 접근성을 높여 시각장애인의 문맹률 감소를 목표로 한다.

• The Journal of the Acoustical Society of Korea
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• v.31 no.6
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• pp.353-358
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• 2012

This paper describes acoustic phonetic parameters for detecting nasal place in a knowledge-based speech recognition system. Initial acoustic phonetic parameters are selected by studying nasal production mechanisms which are radiation of the sound through the nasal cavity. Nasals are produced with differing articulatory configuration which can be classified by measuring acoustic phonetic parameters such as band energy ratio, band energy differences, formants and formant differences. These acoustic phonetic parameters were tested in a classification experiment among labial nasal, alveolar nasal and velar nasal. An overall classification rate of 57.5% is obtained using the proposed acoustic phonetic parameters on the TIMIT database.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.108-115
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• 1996

This paper proposes an algorithm and a model topology for the connected speech recognition using Discrete Hidden Markov Models. A proposed model uses diphone and triphone model which consider the recognition rate and recognisable vocabulary. Considering more exact inter- phoneme segmentation and execution speed of algorithm, 4 states have to exist in diphone model where the first state and the last state are keeping a steady state, the other states hold a transient state. 7 states have to exist in triphone model where 7 states are specified and improved to 3 steady states and 4 transition states. Also, the proposed speech recognition algorithm is designed to detect the inter-phoneme segmentation during the recognition processing.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.2
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• pp.60-65
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• 2002

In this paper, we propose GFCC(gammatone filter frequency cepstrum coefficient) parameter which was based on the auditory characteristic for accomplishing better speech recognition rate. And it is performed the experiment of speech recognition for isolated word acquired from telephone network. For the purpose of comparing GFCC parameter with other parameter, the experiment of speech recognition are carried out using MFCC and LPCC parameter. Also, for each parameter, we are implemented CMS(cepstral mean subtraction)which was applied or not in order to compensate channel distortion in telephone network. Accordingly, we found that the recognition rate using GFCC parameter is better than other parameter in the experimental result.

• The Journal of the Acoustical Society of Korea
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• v.13 no.4
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• pp.32-39
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• 1994

As a basic research to realize Korean speech recognition system, phoneme recognition was carried out to find out ; 1) the best place which represents each phoneme's characteristics, and 2) the reasonable length of duration for obtaining the best recognition rates. For the recognition experiments, multi-speaker dependent recognition with Bayesian decision rule using 21 order of cepstral coefficient as a feature parameter was adopted. It turned out that the best place of feature extraction for the highest recognition rates were 10~50ms in vowels, 40~100ms in fricatives and affricates, 10~50ms in nasals and liquids, and 10~50ms in plosives. And about 70ms of duration was good enough for the recognition of all 35 phonemes.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.161-165
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• 1994

HMM은 좋은 결과를 보이면서 현재 음성 인식 분야에서 널리 사용되는 알고리즘이다. 그러나, 이 HMM의 학습방법인 maimum like-ihood estimation 은 인식률을 극대화하는 모델의 파라메터 값을 생성하지 못하는 단점이 있다. 이러한 문제점을 보와하기 위하여 연결어 인식 알고리즘인 Segmental K-means의 학습과정에 교정 학습법을 도입하여 모델 파라메터 값을 재조정 해 준다. 한국어 연속 숫자음은 영어 연속 숫자음과 달리 연음 현상의 영향을 많이 받는다. Level building 과정에서 연음에 의한 오류를 감소시키기 위해 연음에 의해 발생할 수 있는 단어를 별도의 모델로 추가했다. 이렇게 추가된 단어 모델들에 대한 몇가지 규픽을 인식 결과에 적용하여 출력을 다시 조정한다. 본 시스템은 TMS320C30 프로세서 내장한 DSP 보드와 IBM PC 사엥서 구현되었고, 표준 패턴은 실험실 잡음 환경에서 남성화자 3명을 대상으로 작성하였다. 인식 결과 21종 전화번호 252개 데이터에 대하여 화자 종속으로 92.1% 인식률을 나타내었다.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4
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• pp.47-52
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• 1999

In this paper, we proposed a new approach to weight each feature parameter by considering the dispersion of feature parameters and its degree of contribution to recognition rate. We determined the total distribution factor that is proportional to recognition rate of each feature parameter and the dispersion factor according to the dispersion of each feature parameter. Then. we determined state-dependent weighting using the total distribution factor and dispersion factor. To verify the validity of the proposed approach, recognition experiments were performed using the PLU(Phoneme-Like Unit)-based HMM. Experimental results showed the improvement of 7.7% at the recognition rate using the proposed method.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.16-20
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• 2000

Most of speech recognition systems are using Hidden Markov Model based on statistical modelling frequently. In Korean isolated telephone digit speech recognition, high recognition rate is gained by using HMM if many training data are given. But in Korean continuous telephone digit speech recognition, HMM has some limitations for similar telephone digits. In this paper we suggest a way to overcome some limitations of HMM by using discriminant learning based on minimal classification error criterion in Korean continuous telephone digit speech recognition. The experimental results show our method has high recognition rate for similar telephone digits.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.11-14
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• 2007

인간과 컴퓨터간의 상호교류 하는데 있어서 감정 인식은 필수라 하겠다. 그래서 본 논문에서는 음성 신호 및 얼굴 영상을 BL(Bayesian Learning)과 PCA(Principal Component Analysis)에 적용하여 5가지 감정 (Normal, Happy, Sad, Anger, Surprise) 으로 패턴 분류하였다. 그리고 각각 신호의 단점을 보완하고 인식률을 높이기 위해 결정 융합 방법과 특징 융합 방법을 이용하여 감정융합을 실행하였다. 결정 융합 방법은 각각 인식 시스템을 통해 얻어진 인식 결과 값을 퍼지 소속 함수에 적용하여 감정 융합하였으며, 특정 융합 방법은 SFS(Sequential Forward Selection)특정 선택 방법을 통해 우수한 특정들을 선택한 후 MLP(Multi Layer Perceptron) 기반 신경망(Neural Networks)에 적용하여 감정 융합을 실행하였다.