• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.201-207
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• 2004

This paper is a study on the recognition of continuous speech and uses a method of speech recognition using syntactic analysis and one-stage DMS/DP. In order to perform the speech recognition, first of all, we make DMS model by section division algorithm and let continuous speech data be recognized through One-stage DMS/DP method using syntactic analysis. Besides the speech recognition experiments of proposed method, we experiment the conventional one-stage DP method under the equivalent environment of data and conditions. From the recognition experiments, it is shown that Ole-stage DMS/DP using syntactic analysis is superior to conventional method.

• The Journal of the Acoustical Society of Korea
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• v.13 no.2E
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• pp.41-50
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• 1994

This paper proposes a DMS(Dynamic Multi-Section) model based on the information of the similar features in word pattern. This model represents each word as a time series of several sections and each section implies duration time information and typical feature vectors. The procedure to make a model in the word pattern is that typical feature vector and duration time information are reflected in the distance, when matching between word pattern and model is repeated. As the result of it, the accumulated distance by matching is to be minimized.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.1039-1045
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• 1994

The speech recognition systems using VQ have usually the problem decreasing recognition rate, MSVQ assigning the dissimilar vectors to a segment. In this paper, applying One-stage DMS/DP algorithm to the recognition experiments, we can solve these problems to what degree. Recognition experiment is peformed for Korean DDD area names with DMS model of 20 sections and word unit template. We carried out the experiment in speaker dependent and speaker independent, and get a recognition rates of 97.7% and 81.7% respectively.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.97-104
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• 1995

This paper is a study on the recognition of continuous digits for the implementation of a voice dialing system, and proposes an method of speech recognition using syntactic analysis and One-Stage DP. In order to perform the speech recognition, first of all, we make DMS model by section division algorithm and let continuous digits data be recognized through the proposed One-Stage DP method using syntactic analysis. In this study, 7 continuous digits of 21 kinds which is pronounced by 8 male speakers two or three times, are used. The speaker dependent and speaker independent recognition are performed with the above data by way of the conventional One-Stage DP and the proposed One-Stage DP using syntactic analysis under the condition of laboratory environment. From the recognition experiments, it is shown that the proposed method was better than the established method. And, the recognition accuracy of speaker dependence and independence by the proposed One-Stage DP using syntactic analysis was about 91.7% and 89.7%.

• The Journal of the Acoustical Society of Korea
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• v.12 no.3
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• pp.13-25
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• 1993

본 논문은 음성 다이얼링 시스템을 구현하기 위한 연결어 인식에 관한 연구이다. 적용된 인식 알고리즘은 기준패턴을 생성할 때 DMS 모델을 이용한 One-stage DMS/DP 알고리즘이고, 인식 대상어는 광운대학교 부서명 150 단어이다. 연결어 인식을 실시간으로 처리하기 위한 방법으로써 본 논문에서는 음절과 단어 단위의 DMS 템플리트를 구성하여 실험하였고 이 실험결과로부터 실시간과 인식률을 고려한 최적의 인식은 단어단위 템플리트에서 20 구간의 DMS 템플리트를 구성하여 실험하였고 이 실험결과로부터 실시간과 인식률을 고려한 최적의 인식은 단어단위 템플리트에서 20구간의 DMS 모델을 적용하였을 때 수행되었고, 이때 다중화자종속과 화자독립의 인식률은 각각 97.2%, 86.8%이다. 실험된 결과를 이용하여 음성 다이얼링 모델 시스템을 DSP 전용칩인 TMS320C30 프로세서를 내장한 DSP 보오드, 486 PC와 DIAL 모뎀을 이용해서 구현하였고, 전체 다이얼링 시간은 약 7~14초가 소요되었다.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.51-56
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• 2000

Is this paper, we studied on the automatic speech control system in real-time windows environment using voice recognition. The applied reference pattern is the variable DMS model which is proposed to fasten execution speed and the one-stage DP algorithm using this model is used for recognition algorithm. The recognition vocabulary set is composed of control command words which are frequently used in windows environment. In this paper, an automatic speech period detection algorithm which is for on-line voice processing in windows environment is implemented. The variable DMS model which applies variable number of section in consideration of duration of the input signal is proposed. Sometimes, unnecessary recognition target word are generated. therefore model is reconstructed in on-line to handle this efficiently. The Perceptual Linear Predictive analysis method which generate feature vector from extracted feature of voice is applied. According to the experiment result, but recognition speech is fastened in the proposed model because of small loud of calculation. The multi-speaker-independent recognition rate and the multi-speaker-dependent recognition rate is 99.08% and 99.39% respectively. In the noisy environment the recognition rate is 96.25%.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2E
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• pp.55-61
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• 1997

This paper proposes a MSHMM(Multi-Section Hidden Markov Model) recognition method based on Fuzzy Concept, as a method on the speech recognition of speaker-independent. In this recognition method, training data are divided into several section and multi-observation sequences given proper probabilities by fuzzy rule according to order of short distance from MSVQ codebook per each section are obtained. Thereafter, the HMM per each section using this multi-observation sequences is generated, and in case of recognition, a word that has the most highest probability is selected as a recognized word. In this paper, other experiments to compare with the results of these experiments are implemented by the various conventional recognition methods(DP, MSVQ, DMS, general HMM) under the same data. Through results of all-round experiment, it is proved that the proposed MSHMM based on fuzzy concept is superior to DP method, MSVQ method, DMS model and general HMM model in recognition rate and computational time, and does not decreases recognition rate as 92.91% in spite of increment of speaker number.

• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.3-8
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• 2000

In this paper, we studied design and implementation of a robust speech recognition system in noisy car environment. The reference pattern used in the system is DMS(Dynamic Multi-Section). Two separate acoustic models, which are selected automatically depending on the noisy car environment for the speech in a car moving at below 80km/h and over 80km/h are proposed. PLP(Perceptual Linear Predictive) of order 13 is used for the feature vector and OSDP (One-Stage Dynamic Programming) is used for decoding. The system also has the function of editing the phone-book for voice dialing. The system yields a recognition rate of 89.75% for male speakers in SI (speaker independent) mode in a car running on a cemented express way at over 80km/h with a vocabulary of 33 words. The system also yields a recognition rate of 92.29% for male speakers in SI mode in a car running on a paved express way at over 80km/h.