• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.515-518
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• 2007

SAFRS(Spontaneous Acoustic Field Reproduction System) is a system to sense changes of surroundings and produce sounds which can go well with environment elements sensed by the system in to the space. The sounds were judged by individual evaluation and, the classification of the preferred sounds according to the mood of the space was suggested in the former study. Effectiveness of SAFRS with field application was validated by prior studies which dealt with researching acoustic environment, evaluating images of sounds, and rating environment with existence and nonexistence of sound resources such as fountains and the system after applied in D university. In this study, for more effective field application of SAFRS, research for the acoustic environment around sound resources and subjective evaluation of the preference of the sounds from the resources were made and it was considered that the results of the experiments should be primary information to propose proper sound level to be offered by the system. The results of the study are as follows; 1) It was considered that the ambience of the center road was dependent upon produced sounds by the system and water sounds of the fountain and that of walk way was mostly dependent upon produced sounds. 2) The results of the subjective evaluation showed that the distance from sound resources was suggestive; the more distant from produced sounds the less full and clear the sounds, the less distant from the sounds of water the more delight and idyllic ambience, and the less distant from the forest the more idyllic ambient and diversity. 3) The results upwards were telling that an average value of six elements for the evaluation was even at the place set back 10.2m from center road and walk way. And harmony of all sounds of the place should be considered to propose suitable sound level of SAFRS.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.6 s.123
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• pp.547-552
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• 2007

SAFRS(spontaneous acoustic field reproduction system) is a system to sense changes of surroundings and produce sounds which can go well with environment elements sensed by the system in to the space. The sounds were judged by individual evaluation and, the classification of the preferred sounds according to the mood of the space was suggested in the former study. Effectiveness of SAFRS with field application was validated by prior studies which dealt with researching acoustic environment, evaluating images of sounds, and rating environment with existence and nonexistence of sound resources such as fountains and the system after applied in D university. In this study, for more effective field application of SAFRS, research for the acoustic environment around sound resources and subjective evaluation of the preference of the sounds from the resources were made and it was considered that the results of the experiments should be primary information to propose proper sound level to be offered by the system. The results of the study are as follows; 1) It was considered that the ambience of the center road was dependent upon produced sounds by the system and water sounds of the fountain and that of walk way was mostly dependent upon produced sounds. 2) The results of the subjective evaluation showed that the distance from sound resources was suggestive; the more distant from produced sounds the less full and clear the sounds, the less distant from the sounds of water the more delight and idyllic ambience, and the less distant from the forest the more idyllic ambient and diversity. 3) The results upwards were telling that an average value of six elements for the evaluation was even at the place set back 10.2m from center road and walk way. And harmony of all sounds of the place should be considered to propose suitable sound level of SAFRS.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.691-692
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• 2013

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.145-150
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• 2019

We develop the system realization of whale sound reconstruction by inverse MFCC algorithm with the weighted L2-norm minimization techniques. The output products from this research will contribute to the whale tourism and multimedia content industry by combining whale sound contents with the prototype of 3D printing. First of all, we develop the softwares for generating whale sounds and install them into Raspberry Pi hardware and fasten them inside a 3D printed whale. The languages used in the development of this system are the C++ for whale-sounding classification, MATLAB and Python for whale-sounding playback algorithm, and Rhino 6 for 3D printing.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.362-371
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• 2022

As considerable interests in noise emission from the ships have been increased, International Maritime Organization (IMO) standardized the Underwater Radiated Noise (URN) measurement process of commercial ships in deep seas by enacting the related ISO standard ISO 17208-1 and classification societies responded with the enactment or revision of corresponding notations. According to this trend, a new hybrid underwater sound propagation model based on underwater sound propagation theories was developed and its accuracy on analysis was verified through the result comparison with the results of other generally used models. Using the verified model, each URN propagation characteristics adjusted by the correction methods proposed in the ISO standard and class notations were analyzed and compared in two assumed URN measurement cases. The results showed that the effects of transmission loss corrections in the circumstances with less bottom reflections generally similar but they had rather large differences in the model analysis results with bottom-reflection-dominant conditions. It was concluded that the deep consideration of effective bottom-reflection-correction method should be made in future revisions of ISO standard and class notations.

• Korean Journal of Environment and Ecology
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• v.36 no.3
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• pp.350-357
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• 2022

A national park is a place to conserve natural resources and visitors to experience nature, and thus, it is necessary to identify the noise distribution characteristic in the national park and preserve and restore the soundscape. However, most national parks in Korea are exposed to noise, leading to negative perceptions of the national park's soundscape and affecting the ecosystem. Many national parks in other countries have investigated the ecosystem impacts caused by noise and have performed various management to reduce the noise. However, in Korea, there is still a lack of awareness of the effect on the ecosystem, overlooking the need for soundscape management. Therefore, in this study, we developed a noise map of Mudeungsan National Park to investigate the quantitative impact of noise on visitors and the ecosystem. Also, we measured the trail's soundscape to describe a sound grade classification, and the soundscape of main spots in the park was recorded for a year and then analyzed. Finally, the sound resource distribution map was described, which can be used as preliminary data to determine the national park's sound distribution characteristics and manage the soundscape.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.522-525
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• 2009

This paper proposed the content-based method of classifying filthy Phornographic video, which causes a big problem of modern society as the reverse function of internet. Audio data was used to extract the features from Phornographic video. There are frequency spectrum, autocorrelation, and MFCC as the feature of audio used in this paper. The sound that could be filthy contents was extracted, and the Phornographic was classified by measuring how much percentage of relevant sound was corresponding with the whole audio of video. For the experiment on the proposed method, The efficiency of classifying Phornographic was measured on each feature, and the measured result and comparison with using multi features were performed. I can obtain the better result than when only one feature of audio was extracted, and used.

• Journal of Ocean Engineering and Technology
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• v.34 no.4
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• pp.277-284
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• 2020

Underwater acoustics, which is the study of phenomena related to sound waves in water, has been applied mainly in research on the use of sound navigation and range (SONAR) systems for communication, target detection, investigation of marine resources and environments, and noise measurement and analysis. The main objective of underwater acoustic remote sensing is to obtain information on a target object indirectly by using acoustic data. Presently, various types of machine learning techniques are being widely used to extract information from acoustic data. The machine learning techniques typically used in underwater acoustics and their applications in passive SONAR systems were reviewed in the first two parts of this work (Yang et al., 2020a; Yang et al., 2020b). As a follow-up, this paper reviews machine learning applications in SONAR signal processing with a focus on active target detection and classification.

• Phonetics and Speech Sciences
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• v.4 no.2
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• pp.95-104
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• 2012

Thyroidectomy patients may have vocal paralysis or paresis, resulting in a breathy voice. The aim of this study was to investigate the aerodynamic and acoustic characteristics of a breathy voice in thyroidectomy patients. Thirty-five subjects who have vocal paralysis after thyroidectomy participated in this study. According to perceptual judgements by three speech pathologists and one phonetic scholar, subjects were divided into two groups: breathy voice group (n = 21) and non-breathy voice group (n = 14). Aerodynamic analysis was conducted by three tasks (Voicing Efficiency, Maximum Sustained Phonation, Vital Capacity) and acoustic analysis was measured during Maximum Sustained Phonation task. The breathy voice group had significantly higher subglottal pressure and more pathological voice characteristics than the non breathy voice group. Showing 94.1% classification accuracy in result logistic regression of aerodynamic analysis, the predictor parameters for breathiness were maximum sound pressure level, sound pressure level range, phonation time of Maximum Sustained Phonation task and Pitch range, peak air pressure, and mean peak air pressure of Voicing Efficiency task. Classification accuracy of acoustic logistic regression was 88.6%, and five frequency perturbation parameters were shown as predictors. Vocal paralysis creates air turbulence at the glottis. It fluctuates frequency-related parameters and increases aspiration in high frequency areas. These changes determine perceptual breathiness.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.233-244
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• 2021

Recently, several ICT-based cat studies have produced some successful results, according to academic and industry sources. However, research on the level of simply identifying the cat's condition, such as the behavior and sound classification of cats based on images and sound signals, has yet to be found. In this paper, based on the veterinary scientific knowledge of cats, a practical and academic cat monitoring and disease diagnosis system is proposed to monitor the health status of the cat 24 hours a day by automatically categorizing and analyzing the behavior of the cat with location information using LSTM with a beacon sensor and a raspberry pie that can be built at low cost. Validity of the proposed system is verified through experimentation with cats in actual custody (the accuracy of the cat behavior classification and location identification was 96.3% and 92.7% on average, respectively). Furthermore, a rule-based disease analysis system based on the veterinary knowledge was designed and implemented so that owners can check whether or not the cats have diseases at home (or can be used as an auxiliary tool for diagnosis by a pet veterinarian).