• The Journal of the Acoustical Society of Korea
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• v.37 no.5
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• pp.363-368
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• 2018

Recently a slat type ceiling is widely used in various spaces, such as music performance spaces and concourse of airport and a general reception area of a building. However, it is hard to find a proper design guideline or material useful in designing such spaces, due to the lack of relevant researches on the effect of a slat ceiling on room acoustics. The present work investigated the effect of a slat type ceiling using a physical scale model method. A 1/20 scale model of a small shoe-box type music performance hall was built and a slat ceiling with different configurations was installed. 6 cases of different ceiling configurations were considered with the combination of 2 slat ceiling height cases and 3 distance cases between slats. The effect of a slat ceiling on the acoustics of a room was evaluated by measuring reverberance($T_{30}$), intelligibility and clarity($D_{50}$ and $C_{80}$), and loudness(G and $G_{80}$).

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.291-297
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• 2006

This paper proposes a new Digital Reverberator that models Analog Helical Coil Spring Reverberator for guitar amplifiers. While the conventional digital reverberators are proposed to provide better sound field mainly based on room acoustics, no algorithm or analysis of digital reverberators those model Helical Coil Spring Reverberator was proposed. Considering the fact that approximately $70{\sim}80$ percent of guitar amplifiers are still with Helical Coil Spring Reverberator, research was performed based not on Room Acoustics but on Helical Coil Spring Reverberator itself as an effector. After performing simulations with proposed algorithm, it was confirmed that the Digital Reverberator by proposed algorithm provides perceptually equivalent response to the conventional Analog Helical Coil Spring Reverberators.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.432-440
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• 2009

Recently, the necessity of underwater acoustic communication and demand for transmitting and receiving various data such as voice or high resolution image data are increasing as well. The performance of underwater acoustic communication system is influenced by underwater channel characteristic. Especially, a delay spread caused by reverberation and multi-path induces the ISI (Inter-Symbol-Interference) and reduces the communication performance. In this paper, we study the OFDM (Orthogonal Frequency Division Multiplexing) technique for robust the delay spread in underwater channel. We also use the clipping method to overcome the performance degradation in high PAPR (Peak-to-Average Power Ratio). We confirm the performances of underwater communication system by the underwater channel model simulation model and experiment in small water tank. As a result, the multi-carrier modulation with clipping method presented low BER and the previous single carrier modulation had high BER.

• The Journal of the Acoustical Society of Korea
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• v.34 no.6
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• pp.444-454
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• 2015

Measurements of bottom backscattering strengths in a frequency range of 6-14 kHz were made on the shallow water off the southern Gyeonggi Bay in Yellow Sea in May 2013, as part of the KIOST-HYU joint acoustics experiment. Geological surveys for the experimental area were performed using multi-beam echo sounder, sparker system, and grab sampling to investigate the bottom topography, sub-bottom profile and composition of surficial sediment, respectively. In this paper, the backscattering strengths as a function of grazing angle (in range of $28^{\circ}{\sim}69^{\circ}$) were estimated and compared to the predictions obtained by Lambert's law and APL-UW scattering model. Finally, the effects of geoacoustic parameters corresponding to the experimental area on the backscattering strengths are discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.237-245
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• 2012

This paper describes an acoustic echo canceller with double-talk by the blind signal separation. The acoustic echo canceller is deteriorated or diverged in the double-talk period. So we use the blind signal separation to estimate the near-end speech signal and to eliminate the estimated signal from the residual signal. The blind signal separation extracts the near-end signal with dual microphones by the iterative computations using the 2nd order statistical character. Because the mixture model of blind signal separation is multi-channel in the closed reverberation environment, we used the copied coefficients of echo canceller without computing the separation coefficients. By this method, the acoustic echo canceller operates irrespective of double-talking. We verified performances of the proposed acoustic echo canceller by simulations. The results show that the acoustic echo canceller with this algorithm detects the double-talk periods thoroughly, and then operates stably in the normal state without the divergence of coefficients after ending the double-talking. And it shows the ERLE of averagely 20dB higher than the normal LMS algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.1-8
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• 2010

In this paper, a sound externalization method is proposed for out-of-the-head localization in a headphone listening environment. In order to reduce timbre distortion by the conventional methods using a measured a head-related transfer function (HRTF) or early reflections, the proposed method integrates a model-based HRTF with reverberation. In addition, for improving frontal externalization performance, techniques such as decorrelation and spectral notch filtering are included. To evaluate the performance of the proposed externalization method, subjective listening tests are conducted by using different types of sound sources such as white noise, sound effects, speech, and music. It is shown from the test results that the proposed externalization method can localize sound sources farther away from out of the head than the conventional method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.4
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• pp.426-435
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• 2013

In this paper, we propose the MIMO circular polarization feed network to enhance the communication performances from the previous $2{\times}2$ MIMO channel to $4{\times}4$ channel for Land Mobile Satellite communication system. The only possibility to extend the communication channel is to use the additional satellite because of the limitation of satellite spaces to install additional antennas. For overcoming this problems, we propose the MIMO circular polarization feed network to secure the isolation characteristics without the distant antenna space. The port isolation characteristics and each port impedance matching conditions are numerically verified and we suggest the $4{\times}4$ MIMO channel model of the proposed system and the performances are verified. The fabricated circular polarization patch antennas with the proposed feed network are measured in the reverberation chamber and 7~10 dB of diversity gain and 80 % increasement of channel capacity are obtained.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.4
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• pp.185-194
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• 2013

Abstract- In distant-talking environments, speech recognition performance degrades significantly due to noise and reverberation. Recent work of Michael L. Selzer shows that in microphone array speech recognition, the word error rate can be significantly reduced by adapting the beamformer weights to generate a sequence of features which maximizes the likelihood of the correct hypothesis. In this approach, called Likelihood Maximizing Beamforming algorithm (Limabeam), one of the method to implement this Limabeam is an UnSupervised Limabeam(USL) that can improve recognition performance in any situation of environment. From our investigation for this USL, we could see that because the performance of optimization depends strongly on the transcription output of the first recognition step, the output become unstable and this may lead lower performance. In order to improve recognition performance of USL, some post-filter techniques can be employed to obtain more correct transcription output of the first step. In this work, as a post-filtering technique for first recognition step of USL, we propose to add a Wiener-Filter combined with Feature Weighted Malahanobis Distance to improve recognition performance. We also suggest an alternative way to implement Limabeam algorithm for Hidden Markov Network (HM-Net) speech recognizer for efficient implementation. Speech recognition experiments performed in real distant-talking environment confirm the efficacy of Limabeam algorithm in HM-Net speech recognition system and also confirm the improved performance by the proposed method.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.55-65
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• 2016

Detecting an object which is located at seabed is an important issue for various areas. This paper presents an approach to detection of an object that is placed at seabed in the shallow water. A conventional scheme is to employ a side-scan sonar to obtain images of a detection area and to use image processing schemes to recognize an object. Since this approach relies on high frequency signals to get clear images, its detection range becomes shorter and the processing time is getting longer. In this paper, we consider an active sonar system that is repeatedly sending a linear frequency modulated signal of 6~20 kHz in the shallow water of 100m depth. The proposed approach is to model consecutively received reflected signals and to measure their modeling error magnitudes which decide the existence of an object placed on seabed depending on relative magnitude with respect to threshold value. The feature of this approach is to only require an assumption that the seabed consists of an homogeneous sediment, and not to require a prior information on the specific properties of the sediment. We verify the proposed approach in terms of detection probability through computer simulation.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.