• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.10a
• /
• pp.379-382
• /
• 2008

In order to reduce the noise quantity in a conversation under the noisy environment, it is necessary for the signal processing system to process adaptively according to the noise quantity in order to enhance the performance. There fore this paper presents a recognition method for noise quantity by linear predictive coefficient using a three layered neural network, which is trained using three kinds of speech that is degraded by various background noises. In the experiment, the average values of the recognition results were 97.6% or more for various noises using Aurora2 database.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.40 no.4
• /
• pp.331-341
• /
• 1991

The discrete cosine transform (DCT) is widely used in many signal processing areas, including image and speech data compression. In this paper, we investigate a fixed-point error analysis for fast DCT algorithms, namely, Lee [6], Hou [7] and Vetterli [8]. A statistical model for fixed-point error is analyzed to predict the output noise due to the fixed-point implementation. This paper deals with two's complement fixed-point data representation with truncation and rounding. For a comparison purpose, we also investigate the direct form DCT algorithm. We also propose a suitable scaling model for the fixed-point implementation to avoid an overflow occurring in the addition operation. Computer simulation results reveal that there is a close agreement between the theoretical and the experimental results. The result shows that Vetterli's algorithm is better than the other algorithms in terms of SNR.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.19 no.1
• /
• pp.9-15
• /
• 2016

Source localization has developed in various fields of signal processing including radar, sonar, and wireless communication, etc. Source localization can be found by estimating the time difference of arrival between the each of sensors. Several methods like the NLS(Nonlinear Least Square) cost function have been proposed in order to improve the performance of time delay estimation. In this paper, we propose a clustering method using the four sensors with the same aperture as previous methods of using the three sensors. Clustering method can be improved the source localization performance by grouping similar estimated values. The performance of source localization using clustering method is evaluated by Monte Carlo simulation.

• MALSORI
• /
• no.61
• /
• pp.49-62
• /
• 2007

This study focused on the improvement of prosody transplantation technology to be used for effective prosody education. Issues making the technology a less acceptable tool for prosody education were addressed. Instead of merely copying the target pitch onto a learner's utterances, the target pitch was resealed in semitone before the transplantation. In so doing, distortion of a signal was minimized and the transplanted utterance could have the quality of sound not different from the learner's utterances. Instead of manual transplantation, an automatic procedure was proposed to increase the reliability and the consistency of the outcome and enable real time processing. The perceptual performance of the automatic transplantation was evaluated by the perception experiment showing the automatic ransplantation was as good as the manual process.

• Journal of Sensor Science and Technology
• /
• v.21 no.2
• /
• pp.144-150
• /
• 2012

A microphone for fully implantable hearing device was generally implanted under the skin of the temporal bone. So, the implanted microphone's characteristics can be affected by the accompanying noise due to masticatory movement. In this paper, the implantable microphone with 2-channels structure was designed for reduction of the generated noise signal by masticatory movement. And an experimental model for generation of the noise by masticatory movement was developed with considering the characteristics of human temporal bone and skin. Using the model, the speech signal by a speaker and the artificial noise by a vibrator were supplied simultaneously into the experimental model, the electrical signals were measured at the proposed microphone. The collected signals were processed using a general adaptive filter with least mean square(LMS) algorithm. To confirm performance of the proposed methods, the correlation coefficient and the signal to noise ratio(SNR) before and after the signal processing were calculated. Finally, the results were compared each other.

• The Journal of the Acoustical Society of Korea
• /
• v.16 no.1
• /
• pp.81-87
• /
• 1997

In this paper, a new pre-processing method for the recognition of single vowels by use of spectrum envelope is presented. We use new extraction method of a spectrum envelope using the diffusion filter bank. By dividing analysis band of a diffusion filter bank into subbands, we decreased the number of diffusion process. And, by increasing the number of difference, we got higher selectivity. As a result of them, we reduced the total processing time, and got higher enhancement of discrimination. By getting 88.3% of average recognition rate for single vowels of natural voice through computer simulation. We confirmed it to be useful for speech recognition which use spectrum analysis of the voice signal to have many frequency components.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.11a
• /
• pp.117-120
• /
• 2007

개인의 체질에 맞춰 의학적 행위를 시행하는 사상의학은 우리나라 고유의 전통의학으로 가치를 인정받고 있다. 이러한 사상의학에서 가장 중요한 것은 사상체질의 정확한 분류이다. 본 논문에서는 기존의 사상체질 분류 방법인 용모사기, 체형기상, QSCCII, 체질침 등이 임상의들의 직관에 의해 행해지고 있다는 문제점을 해결하기 위해 사상체질 분류의 정량화 및 객관화를 위한 연구를 수행하였다. 이를 위해 본 논문에서는 음성 신호 분석에서 발생하는 정보의 출력값에 의해 사상 체질을 분류하는 방법을 제안하였다. 이를 위해 40대 이상의 장년기 남성을 대상으로 사상체질 전문의의 진단표에서 뚜렷한 특징을 보유하고 있는 집단군을 구성하고 이들의 음성 특성을 분류하여 음성학적 요소를 추출하고자 한다. 또한 출력된 결과값을 토대로 체질 집단별 차이점과 유사성을 분류하여 사상 체질 분류를 행하였다.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.5
• /
• pp.174-180
• /
• 2015

In this paper, we propose the passive sonar signal processing technique for estimating target information using proximity sensor. This algorithm is performed by single sensor which is constituted underwater sensor network and has a hierarchical structure. The estimated parameter is the velocity, the depth, the distance and bearing at CPA situations and we can improve the accuracy of signal processing techniques through having a hierarchical structure. We verify the performance of the proposed method by computer simulation and then we check the result that 20% error can be occurred in maximum detectable range. We also confirm that proposed method has the reliability in the actual sea environment through the sea experiment.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.4 no.5
• /
• pp.963-969
• /
• 2000

In this paper, we define two input-output gains of linear periodic time-varying systems. One is the ratio of output with worst-case l2-norm over all inputs with unit 12-norm. It denotes G($\iota_2,\iota_2$.The other is the ratio of output with worst-case RMS value over all inputs with unit RMS value. It denotes G(RMS, RMS) .It is fact that these two gains are equivalent for linear time-invariant system. In this paper, we prove these two gains are also equivalent for linear periodic time-varying system. In addition, the relationship between two method of obtaining the generalized frequency responses for linear periodic time-varying system is derived. Finally, we apply the defined input-output gains to M-channel filter-bank which is multi-rate signal Processing system, used to speech coding. In the filter-bank, generally, aliasing distortion, magnitude distortion, and phase distortion are present. It is shown that these are kept small if the filter-bank is designed by a method that optimizes the gain G($\iota_2,\iota_2$ of an error system.

• Journal of Korea Multimedia Society
• /
• v.3 no.4
• /
• pp.347-355
• /
• 2000

This paper presents an adaptive AEC(acoustic echo canceller) based on the wavelet transform using M-channel subband QMF filter banks. The proposed algorithm improves the performance of AEC with a realtime process by a low complexity of wavelet transform filter banks, a subband processing and a orthogonality of wavelet subband filter. Adaptive filter coefficients of each subband are updated using LMS algorithm with a low complexity and a easy realization for a realtime processing and a reduction of hardware cost. For a input signal, a white Gaussian noise and a real speech signal with a environment noises are used for a performance estimation of the proposed algorithm. As a result of computer simulation, the proposed AEC has a low asymptotic error, a low computation complexity and a robust performance.