• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.8
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• pp.759-766
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• 2016

This paper is on a system design of recognizing sound sources and tracing locations from detecting a section of sound sources which is strong in surrounding environmental sounds about sound sources occurring in an abnormal situation by using signals within the section. In detection of the section with strong sound sources, weighted average delta energy of a short section is calculated from audio signals received. After inputting it into a low-pass filter, through comparison of values of the output result, a section strong in background sound is defined. In recognition of sound sources, from data of the detected section, using an HMM(: Hidden Markov Model) as a traditional recognition method, learning and recognition are realized from creating information to recognize sound sources. About signals of sound sources that surrounding background sounds are included, by using energy of existing signals, after detecting the section, compared with the recognition through the HMM, a recognition rate of 3.94% increase is shown. Also, based on the recognition result, location grasping by using TDOA(: Time Delay of Arrival) between signals in the section accords with 97.44% of angles of a real occurrence location.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.155-160
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• 2021

This paper proposes an automatic method for detecting snore sound, one of the important symptoms of sleep apnea patients. In the proposed method, sound signals generated during sleep are input to detect a sound generation section, and a spectrogram transformed from the detected sound section is applied to a classifier based on a Convolutional Bidirectional Gated Recurrent Unit (CBGRU) with attention mechanism. The applied attention mechanism improved the snoring sound detection performance by extending the CBGRU model to learn discriminative feature representation for the snoring detection. The experimental results show that the proposed snoring detection method improves the accuracy by approximately 3.1 % ~ 5.5 % than existing method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.81-88
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• 2010

In this paper, we proposed an automatic music/non-music signal discrimination system from broadcasting audio signal as a preliminary study of building a sound source monitoring system in real broadcasting environment. By reflecting human speech articulation characteristics, we used three simple time-domain features such as energy standard deviation, log energy standard deviation and log energy mean. Based on the experimental threshold values of each feature, we developed a rule-based algorithm to classify music portion of the input audio signal. For the verification of the proposed algorithm, actual FM broadcasting signal was recorded for 24 hours and used as source input audio signal. From the experimental results, the proposed system can effectively recognize music section with the accuracy of 96% and non-music section with that of 87%, where the performance is good enough to be used as a pre-process module for the a sound source monitoring system.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.12-22
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• 2017

It is important to predict accurately reverberation level, which is a limiting factor in underwater target detection. Recently, the studies have been expanded from monostatic sonar to bistatic sonar in which source and receivers are separated. To simulate the bistatic reverberation level, the computation processes for propagation, scattering strength, and scattering cross section are different from those in monostatic case and more complex computation processes are required. Although there have been many researches for bistatic reverberation, few studies have assessed the bistatic scattering cross section which is a key factor in simulate reverberation level. In this paper, a new method to estimate the bistatic scattering cross section is suggested, which uses the area of intersection between two circles. Finally, the reverberation levels simulated with the scattering cross section estimated using the method suggested in this paper are compared with those estimated using the methods previously suggested and those measured from an acoustic measurements conducted in May 2013.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.57-65
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• 2006

In general, the investigation for reservoir dredging are conducting a observation on the horizontal position and the depth of water by assembling GPS/Echo Sounder and Total Station/Echo Sounder, and it is computed at a section computation of riverbed, reservoir volume and dredging plan etc. at that times, the detail plane is determinated about soil volume, height for dredging. Planning has a fault that the method of sound detection using the Echo Sounder doesn't check up distribution of reservoir deposit. In this study, the author emphasizes that implementation of dredging with combined Global Positioning System(GPS) and Ground Penetration Radar(GPR) is well-done more than existed GPS/Echo Sounder. the combined equipment can be adapted to computation and dredging reffering to distribution of deposition. First of all, it is executed water tank modelling test through sampling for apply to test area and is estimated the possibility after passed far accuracy verification of equipment.

• Journal of the Korean Institute of Gas
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• v.4 no.3 s.11
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• pp.59-64
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• 2000

The real time monitoring system is developed to detect third party damage imposed on natural gas pipeline and to estimate a damage position in section of pipeline in need of monitoring the third party damage. The monitoring system uses wireless data communication in order to build up data communication network. The availability of monitoring system was evaluated through full scale field damage test at Masan's submarine gas pipeline. It was turned out that the estimation error was one percentage of the propagation speed of damage sound in the gas pipeline.