• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1663-1669
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• 1995

This paper is a study on the recognition of Korean proverb using neural network and Markov model. The neural network uses, at the stage of training neurons, features such as the rate of zero crossing, short-term energy and PLP-Cepstrum, covering a time of 300ms long. Markov models were generated by the recognized phoneme strings. The recognition of words and proverbs using Markov models have been carried out. Experimental results show that phoneme and word recognition rates are 81. 2%, 94.0% respectively for Korean proverb recognition experiments.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2212-2215
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• 2003

In this paper, we proposed speech feature vector extractor for embedded system using TMS 320C31 DSP chip. For this extractor, we used algorithm using cepstrum coefficient based on LPC(Linear Predictive Coding) that is reliable algorithm to be is widely used for speech recognition. This system extract the speech feature vector in real time, so is used the mobile system, such as cellular phones, PDA, electronic note, and so on, implemented speech recognition.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4E
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• pp.41-47
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• 1998

Microphone is the first link in the speech recognition system. Depending on its type and mounting position, the microphone can significantly distort the spectrum and affect the performance of the speech recognition system. In this paper, characteristics of the speech signal for different microphones and microphone distances are investigated both in time and frequency domains. In the time domain analysis, the average signal-to-noise ration is measure ration is measured for the database we collected depending on the microphones and microphone distances. Mel-frequency spectral coefficients and mel-frequency cepstrum are computed to examine the spectral characteristics. Analysis results are discussed with our findings, and the result of recognition experiments is given.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.153-156
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• 2003

본 연구는 화자종속 소어휘 음성인식의 성능을 개선하는 데 그 목적이 있다. 인식에 사용될 음성의 특징을 얻기 위해 Winer 필터와 LPC＆Cepstrum을 이용하여 프레임 당 12차 패턴을 추출하였다. 추출된 특징패턴을 인식하는 인식부는 특히 소어휘 음성인식에 우수한 성능을 보이는 기존의 역전파 신경회로망(Backpropagation Neural Network)에 인식율 개선을 위하여 퍼지추론시스템을 결합한 형태로 구현되었다. 실험결과 신경망만을 사용한 경우에 비하여 인식율이 향상됨을 연구하였다.

• Journal of Biomedical Engineering Research
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• v.11 no.2
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• pp.249-256
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• 1990

In this study, LPC cepstrum coefficients are used as feature vector extracted from AR model of EMG signal, and a reduced-connection network whlch has reduced connection between nodes is constructed to classify and recognize EMG functional classes. The proposed network reduces learning time and improves system stability Therefore it is Ehown that the proposed network is appropriate in recognizing function of EMG signal.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.11a
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• pp.129-133
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• 1997

카메라로부터 얻은 영상은 이를 얻는 과정에서 카메라의 떨림 및 추가되는 노이즈에 의하여 손상을 입을 수 있으며, 이런 과정으로 손상된 영상에는 움직임 번짐현상(motion blur)이 발생하며 이는 영상의 명확도를 현저하게 떨어지게 한다. 움직임 번짐현상은 주파수 영역에서 움직임의 방향으로 주기적인 영점을 발생시키며 그 주기는 움직임의 길이에 반비례한다. 이러한 영점은 원 영상에 의한 영점과 노이즈에 의하여 소실되므로 이들의 영향을 power 영역에서의 평균법으로 최소화시킬 필요가 있다. 본 논문에서는 원영상과 노이즈의 영향인 최소화된 상태에서 2차원 cepstrum을 통하여 번짐현상을 주기와 방향을 계산해내는 알고리즘을 제안한다.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.620-623
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• 1988

A vowel is based on the recognition of a phoneme. Thus it is necessary for the programming of an algorithm to achieve the speech recognition in that case. In this paper, cepstrum is used for a voiced-unvoiced decision and speech parameters are extracted by linear prediction coding. Using these parameters, a speech understanding algorithm has been developed.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.511-514
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• 2003

The human being uses speech signals to exchange information. When background noise is present, speech recognizers experience performance degradations. Speech recognition through speech enhancement in the noisy environment was studied. Histogram method as a reliable noise estimation approach for spectral subtraction was introduced using MFCC method. The experiment results show the effectiveness of the proposed algorithm.

• The Journal of the Acoustical Society of Korea
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• v.8 no.5
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• pp.102-112
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• 1989

In this paper, we proposed the study on speaker-independent isolated word recognition for DDD area-name using vector quantization and chose total 146 DDD area-name to recognize words for application of dialing system. We made the codebook using 12th LPC cepstrum coefficients and used the minsum and the minimax method to find the centroid and we applied 3 splitting rule to a codebook generation. The single section and the multi section with time information were used to generate the codebooks and the over-lapped section codebook was used, too. From the experiment result, we proved that the minsum method was better than the minimax method and the evaluation of the system yielded an accuracy of about 90 percents In case of speaker-independent.

• Journal of the Korea Computer Industry Society
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• v.5 no.4
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• pp.491-502
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• 2004

In this paper, we propose a HMM model using FSVQ(First Section VQ), fuzzy theory and doubly spectral feature, as study on the isolated word recognition system of speaker-independent. In the proposed paper, LPC cepstrum coefficients and regression coefficients of LPC cepstrum as doubly spectral feature be used. And, training data are divided several section and first section is generated codebook of VQ, and then is obtained multi-observation sequences by order of large propabilistic values based on fuzzy nile from the codebook of the first section. Thereafter, this observation sequences of first section is trained and is recognized a word to be obtained highest probaility by same concept. Besides the speech recognition experiments of proposed method, we experiment the other methods under the equivalent environment of data and conditions. In the whole experiment, it is proved that the proposed method is superior to the others in recognition rate.