• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.964-969
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• 2008

This paper proposes a HMM-based recognition method using DMSVQ(Dynamic Multi-Section Vector Quantization) codebook by DMS(Dynamic Multi-Section) model and fuzzy concept, as a study for speaker- independent speech recognition. In this proposed recognition method, training data are divided into several dynamic section and multi-observation sequences which are given proper probabilities by fuzzy rule according to order of short distance from DMSVQ codebook per each section are obtained. Thereafter, the HMM 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. Other experiments to compare with the results of recognition experiments using proposed method are implemented as a data by the various conventional recognition methods under the equivalent environment. Through the experiment results, it is proved that the proposed method in this study is superior to the conventional recognition methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.4
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• pp.649-655
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• 2006

This paper proposes a HMM-based recognition method using DMSVQ(Dynamic Multi-Section Vector Quantization) codebook by DMS model and double spectral feature, as a method on the speech recognition of speaker-independent. LPC cepstrum parameter is used as a instantaneous spectral feature and LPC cepstrum's regression coefficient is used as a dynamic spectral feature These two spectral features are quantized as each VQ codebook. HMM using DMS model is modeled by receiving instantaneous spectral feature and dynamic spectral feature by input. Other experiments to compare with the results of recognition experiments using proposed method are implemented by the various conventional recognition methods under the equivalent environment of data and conditions. Through the experiment results, it is proved that the proposed method in this paper is superior to the conventional recognition methods.

• 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.

• 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.

• 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%.

• 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.

• Proceedings of the Acoustical Society of Korea Conference
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• 1991.06a
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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.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.47-50
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• 1998

본 논문은 자동차의 편의성 및 안전성의 동시 확보를 위하여, 보조적 스위치의 조작없이 상시 음성의 입,출력이 가능하도록 하며, band pass filter를 이용하여 잡음환경에서 자동으로 정확하게 음성구간 검출(End Point Detection)을 하게 하였다. Reference Pattern은 Dynamic Multi-Section(DMS)[1] 모델을 사용하였고 차량의 속도에 따라 자동으로 잡음환경에 강인한 모델을 선택하도록 하였으며, 음성의 특징 파라미터와 인식 알고리즘은 Perceptual Linear Predictive(PLP) 13차와 One Stage Dynamic Programming(OSDP)를 사용하였다. 주행중인 자동차 환경(30~70km/h)에서 자주 사용되는 차량제어 명령 33개에 대하여 화자독립 92.98%, 화자종속 94.44% 인식율을 구하였다. 또한 주행중인 차량에서 카폰, 핸드폰 사용으로 인한 사고를 줄이기 위하여 음성으로 전화를 걸 수 있도록 하는 Voice Dialing 기능도 구현하였다.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.97-100
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• 1999

본 논문은 자동차의 편의성 및 안전성의 동시 확보를 위하여, 보조적 스위치의 조작없이 상시 음성의 입$\cdot$출력이 가능하도록 하였고, 남성과 여성을 구별하기 위하여 피치검출법을 사용하여 속도별로 구분하였다. 또한, band pass filter를 이용하여 자동으로 잡음하에서 정확하게 음성추간 검출(End Point Detection)을 하게 하였다. Reference Pattern은 DMS(Dynaminc Multi-Section)[1]모델을 사용하려고, 음성의 특징 파라미터와 인식 알고리즘은 PLP 13차와 One Stage Dynamic Programming(OSDP)를 사용하였다. 시내주행중인 자동차 환경에서 자주 사용되는 차량제어 명령어 30단어를 가지고 실험한 결과 40-80km에서 화자독립 남성 $96\%$, 여성 $94.4\%$ 화자종속일 때 남성 $97\%$, 여성 $95\%$의 인식률을 얻을수 있었고 남성과 여성을 구분하므로 써 인식률을 향상 시켰다.

• 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%.