• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.339-341
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• 1997

This study is presenting the method for an effective data transmission in MAGLEV which is now tested and intends to provide for an intelligent operation of signal system in future. To exchange a lot of information, it is ideal to adopt a digital system and a micro-based system is essential for these purposes. FSK modulation and HDLC protocol are adopted on this study and information line assembly which is used as the information exchange, as the speech communication, and as the detection of speed and position is constructed in one unit. Actually this study is produced academic achievements of the data transmission system of MAGLEV train and an advanced method of intelligent operation in future railway system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.9 no.1
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• pp.30-38
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• 1984

In this paper, we designed the programmable 2nd order switched capacitor filter that the center frequency can be varied linearly with the clock frequency, and that the peak gaion and the selectivity can be controlled with digital signal by the capacitor array. In addition, speech synthesizer system was constructed with this filter, korean consonants being synthesized. Therefore, this filter shows the possibility that most Korean language sounds can be synthesized in the real time mode.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.171-174
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• 2000

본 논문에서는 홈 오토메이션 시스템을 음성인식을 도입하여 설계하였다. 많은 계산량과 방대한 양의 데이터의 처리를 요구하는 음성인식을 DSP(Digital Signal Processor)를 통하여 구현해 보고자 본 연구를 수행하였다. 이를 위해 실시간 끝점검출기를 이용하여 추가의 입력장치가 필요하지 않도록 시스템을 구성하였다. 특징벡터로는 LPC로부터 유도한 10차의 cepstrum과 log 스케일 에너지를 이용하였고, 음소수에 따라 상태의 수를 다르게 구성한 DHMM(Discrete Hidden Marcov Model)을 인식기로 사용하였다. 인식단어는 가정 자동화를 위하여 많이 쓰일 수 있는 10개의 단어를 선택하여 화자 독립으로 인식을 수행하였다. 또한 단어가 인식이 되면 인식된 단어에 대해서 현재의 상태를 음성으로 알려주고 이에 대해 자동으로 실행하도록 시스템을 구성하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.260-261
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• 2010

본 논문에서는 제작된 콘텐츠에 배경음을 간편하고 효과적으로 혼합하기 위해서 녹음된 신호(전경음)를 분석하여 배경음 에너지를 적응적으로 조절하는 배경음혼합 알고리즘을 제안한다. 이를 위해, 제안된 알고리즘은 등청감 곡선 (equal-loudness curve) 및 linear prediction (LP) 분석에 기반하여 전경음신호의 청감 에너지 및 음성신호 존재여부를 결정한다. 이에 따라 전경음에 음성신호가 존재하는 경우에는 음성이 명확하게 들릴 수 있도록 혼합된 배경음의 에너지를 하향 조절하고, 반대로 전경음에 음성신호가 존재하지 않는 경우에는 배경음이 명확하게 들릴 수 있도록 혼합된 배경음의 에너지를 상향 조절한다. 제안된 알고리즘의 효율성을 검증하기 위해, 고정 가중치를 이용하여 배경음을 혼합하는 경우와의 음질 선호도 조사를 실시한 결과, 제안된 알고리즘에 대한 높은 선호도를 보였다.

• The Journal of the Acoustical Society of Korea
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• v.21 no.7
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• pp.606-613
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• 2002

In this paper we applied a transmit beamforming technique to the underwater acoustic communication system for high rate data transmission. A prototype transmit system was designed and implemented with the general purpose DSP processor and multiple digital-to-analog converters. The performances of the implemented system were evaluated by the experiment in water tank. In order to simplify the procedure the channel coding and equalizer were omitted. And the simplest OOK (On-Off Keying) technique in digital communication methods was applied. The experimental result shows that the transmission data rate is higher about 3 times in the case of 5 hydrophone transmitting may than 1 hydrophone transmitter at bit error rate 10/sup -2/. We verified that the maximum data rate was 400 bps for speech signal transmission in water tank.

• The Journal of the Acoustical Society of Korea
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• v.21 no.7
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• pp.648-655
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• 2002

This paper describes implementation of a multi-channel G.723.1 Annex A (G.723.1A) focused on code optimization using a high performance general purpose Digital Signal Processor (DSP), To implement a multi-channel G.723.1A functional complexities of the ITU-T G.723.1A fixed-point C-code are measures an analyzed. Then we sort and optimize C functions in complexity order. In parallel with optimization, we verify the bit-exactness of the optimized code using the ITU-T test vectors. Using only internal memory, the optimized code can perform full-duplex 17 channel processing. In addition, we further increase the number of available channels per DSP into 22 using fast codebook search algorithms, referred to as bit -compatible optimization.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.102-110
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• 2017

In this paper, we have implemented an real-time adaptive feedback cancellation(AFC) algorithm that can be applied to multi-channel digital hearing aid. Multichannel digital hearing aid typically use the FFT filterbank based Wide Dynamic Range Compression(WDRC) algorithm to compensate for hearing loss. The implemented real-time acoustic feedback cancellation algorithm has one integrated structure using the same FFT filter bank with WDRC, which can be beneficial in terms of computation affecting the hearing aid battery life. In addition, when the AFC fails to operate due to nonlinear input and output, the reduction gain is applied to improve robustness in practical environment. The implemented algorithm can be further improved by adding various signal processing algorithm such as speech enhancement.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.103-112
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• 1999

In this paper, a speaker-independent isolated world recognition system for a car navigation system is implemented using a general digital signal processor. This paper presents a method combining SNR normalization with RAS as a noise processing method. The semi-continuous hidden markov model is adopted and TMS320C31 is used in implementing the real-time system. Recognition word set is composed of 69 command words for a car navigation system. Experimental results showed that the recognition performance has a maximum of 93.62% in case of a combination of SNR normalization and spectral subtraction, and the performance improvement rate of the system is 3.69%, Presented noise processing method showed good speech recognition performance in 5dB SNR in car environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.538-542
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• 2018

Echo generated in digital hearing aid vent give rise to user's discomfort. For cancelling feedback echo in vent, it is required to estimate vent impulse response exactly. The vent impulse response has time varying and sparse characteristics. The IPNLMS has been known a useful adaptive algorithm to estimate vent impulse response with these characteristics. In this paper, subband sparse adaptive filter which applying IPNLMS to subband hearing aid structure is proposed to cancel echo of vent by estimating sparse vent impulse response. In the propose method, the decomposition of input signal to subband can pre-whiten each subband signal, so adaptive filter convergence speed can be improved. And the poly phase component decomposition of adaptive filter increases sparsity of each components, and the better echo cancellation can be possible without additional computation. To derive coefficients update equation of the adaptive filter, by defining the cost function based weight NLMS is defined, and the coefficient update equation of each subband is derived. For verifying performances of the adaptive filter, convergence speed, and steady state error by white signal input, and echo cancelling results by real speech input are evaluated by comparing conventional adaptive filters.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.821-827
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• 2018

Affective computing has gained increasing interest in the recent years with the development of potential applications in Human computer interaction (HCI) and healthcare. Although momentous research has been done on human emotion recognition, however, in comparison to speech and facial expression less attention has been paid to physiological signals. In this paper, Electroencephalogram (EEG) signals from different brain regions were investigated using modified wavelet energy features. For minimization of redundancy and maximization of relevancy among features, mRMR algorithm was deployed significantly. EEG recordings of a publically available "DEAP" database have been used to classify four classes of emotions with Multi class Support Vector Machine. The proposed approach shows significant performance compared to existing algorithms.