• Science of Emotion and Sensibility
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• v.3 no.2
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• pp.17-28
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• 2000

Psychoacoustic characteristics of automobile horns play significant role in resulting subjective evaluation and psychphysiological reactions. However, comparison and differentiation of physiological responses to commercially available horns is a complicated task due to the small contrast in technical features of horns and the influence of such processes as habituation on physiological outcome with the increased number of auditory stimulation trials. In a study on 10 college students, there was performed comparative analysis of reactivity of physiological responses mediated by central and autonomic nervous systems in order to identify the role of habituation on decrement of psychophysiological responsivity and assess the ability to differentiate subjectively most and least preferred, as well as most and least appropriate horns according to physiological manifestations. The EEG and autonomic responses to 7 automobile horns were analyzed during 3 blocks of trials, with varying order of stimuli and changed acoustic parameters of horns in each block. Thus, responses were analyzed for totally 21 trials of auditory stimulation. It was shown that electrodermal and cardiovascular responses have different reactivity patterns to repeated stimulation: skin conductance measures habituated, cardiac reactivity showed no signs of habituation, and the vascular response demonstrated sensitization. The temporal EEG exhibited marked habituation of fast beta band power, while alpha-blocking effect did not habituate during the course of experiment. Differentiation of physiological responses of most and least preferred and appropriate horns was possible in our study, however, some cardiovascular reactivity measures differentiated during the entire course of the experiment, while EEG and electrodermal parameters showed significant differences only during first block of trials, and were later affected by the habituation.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.78-83
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• 2019

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.

• The Journal of the Acoustical Society of Korea
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• v.33 no.3
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• pp.174-183
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• 2014

When a active sonar signal is transmitted and returned back from a target, it has been distorted by various properties of acoustic channel such as multipath arrivals. And signals have been appeared to be different form by target position and attitude. Therefore, we simulated the target echo signal using 3 dimensional target model include reflects target features. In this paper, we develop components form of a simulated target model is made up equally spaced highlight points, and each part of the target consists of shape function. We can simulate a target echo signal and Target strength (TS) according to wave incident angle. To verify, we made small scale target in kit form and we had got underwater target signal for comparing simulation result in water tank.

• The Journal of the Acoustical Society of Korea
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• v.35 no.6
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• pp.491-500
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• 2016

The present study describes the acoustical characteristics of the new noise barriers which can control not only noise but also wind pressure by allowing air flow through barriers. In order to investigate the sound reduction index of the air transparent noise barrier, 17 models in total were examined with various size of openings and the volume of the resonators. As a result, it was found that the sound reduction index varies with the volume of the resonator and the area of the openings. Also, it was revealed that double layer of units has more sound reduction index than the single layer of unit at the frequency band from 400 Hz to 1250 Hz. This denoted that physical features of openings and resonators affect the sound reduction index of the air transparent noise barrier.

• Phonetics and Speech Sciences
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• v.2 no.2
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• pp.3-16
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• 2010

This study aims at setting the hierarchy of difficulty of the 7 Korean monophthongs for Mongolian learners of Korean according to Prator's theory based on the Contrastive Analysis Hypothesis. In addition to that, it will be shown that the difficulties and errors for Mongolian learners of Korean as a second or foreign language proceed directly from this hierarchy of difficulty. This study began by looking at the speeches of 60 Mongolians for Mongolian monophthongs; data were investigated and analyzed into formant frequencies F1 and F2 of each vowel. Then, the 7 Korean monophthongs were compared with the resultant Mongolian formant values and are assigned to 3 levels, 'same', 'similar' or 'different sound'. The findings in assessing the differences of the 8 nearest equivalents of Korean and Mongolian vowels are as follows: First, Korean /a/ and /$\wedge$/ turned out as a 'same sound' with their counterparts, Mongolian /a/ and /ɔ/. Second, Korean /i/, /e/, /o/, /u/ turned out as a 'similar sound' with each their Mongolian counterparts /i/, /e/, /o/, /u/. Third, Korean /ɨ/ which is nearest to Mongolian /i/ in terms of phonetic features seriously differs from it and is thus assigned to 'different sound'. And lastly, Mongolian /$\mho$/ turned out as a 'different sound' with its nearest counterpart, Korean /u/. Based on these findings the hierarchy of difficulty was constructed. Firstly, 4 Korean monophthongs /a/, /$\wedge$/, /i/, /e/ would be Level 0(Transfer); they would be transferred positively from their Mongolian counterparts when Mongolians learn Korean. Secondly, Korean /o/, /u/ would be Level 5(Split); they would require the Mongolian learner to make a new distinction and cause interference in learning the Korean language because Mongolian /o/, /u/ each have 2 similar counterpart sounds; Korean /o, u/, /u, o/. Thirdly, Korean /ɨ/ which is not in the Mongolian vowel system will be Level 4(Overdifferentiation); the new vowel /ɨ/ which bears little similarity to Mongolian /i/, must be learned entirely anew and will cause much difficulty for Mongolian learners in speaking and writing Korean. And lastly, Mongolian /$\mho$/ will be Level 2(Underdifferentiation); it is absent in the Korean language and doesn‘t cause interference in learning Korean as long as Mongolian learners avoid using it.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.987-994
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• 2020

In this paper, we studied the effect of kernel size of CNN layer on performance in acoustic noise attenuators. This system uses a deep learning algorithm using a neural network adaptive prediction filter instead of using the existing adaptive filter. Speech is estimated from a single input speech signal containing noise using a 100-neuron, 16-filter CNN filter and an error back propagation algorithm. This is to use the quasi-periodic property in the voiced sound section of the voice signal. In this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed to verify the performance of the noise attenuator for the kernel size. As a result of the simulation, when the kernel size is about 16, the MSE and MAE values are the smallest, and when the size is smaller or larger than 16, the MSE and MAE values increase. It can be seen that in the case of an speech signal, the features can be best captured when the kernel size is about 16.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.161-168
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• 2021

In this paper, a Silent Speech Interface (SSI) technology was proposed in which Doppler frequency shifts of the reflected signal were used to synthesize the speech signals when 40kHz ultrasonic signal was incident to speaker's mouth region. In SSI, the mapping rules from the features derived from non-speech signals to those from audible speech signals was constructed, the speech signals are synthesized from non-speech signals using the constructed mapping rules. The mapping rules were built by minimizing the overall errors between the estimated and true speech parameters in the conventional SSI methods. In the present study, the mapping rules were constructed so that the distribution of the estimated parameters is similar to that of the true parameters by using Generative Adversarial Networks (GAN). The experimental result using 60 Korean words showed that, both objectively and subjectively, the performance of the proposed method was superior to that of the conventional neural networks-based methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1516-1529
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• 2023

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

• Korean Journal of Radiology
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• v.21 no.5
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• pp.605-613
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• 2020

Objective: To determine the malignancy risk of isolated macrocalcifications (a calcified nodule with complete posterior acoustic shadowing) detected on ultrasonography (US) and to evaluate the postoperative American Thyroid Association (ATA) risk stratification of malignant tumors manifesting as isolated macrocalcifications. Materials and Methods: A total of 3852 thyroid nodules (≥ 1 cm) of 3061 consecutive patients who had undergone biopsy between January 2011 and June 2018 were included in this study. We assessed the prevalence, malignancy rate, and size distribution of isolated macrocalcifications and evaluated the histopathologic features and postoperative ATA risk stratification of malignant tumors manifesting as isolated macrocalcifications. Results: Isolated macrocalcifications were found in 38 (1.2%) of the 3061 patients. Final diagnosis was established in 30 (78.9%) nodules; seven malignant tumors were diagnosed as papillary thyroid carcinomas (PTCs). The malignancy rate of the isolated macrocalcifications was 23.3% in the 30 nodules with final diagnoses and 18.4% in all nodules. Among the six surgically-treated malignant tumors, five (83.3%) had an extrathyroidal extension (ETE) (minor ETE 1, gross ETE 4), and two (33.3%) had macroscopic lymph node metastasis. Four (66.7%) malignant tumors were categorized as high-risk tumors, one as an intermediate-risk tumor, and one as a low-risk tumor using the ATA risk stratification. Histopathologically, out of the six malignant tumors, ossifications were noted in four (66.7%) and predominant calcifications in two (33.3%). Conclusion: The US pattern of isolated macrocalcifications (≥ 1 cm) showed an intermediate malignancy risk (at least 18.4%). All malignant tumors were PTCs, and most showed an aggressive behavior and a high or intermediate postoperative ATA risk.

• Journal of the Korean Society of Radiology
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• v.85 no.4
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• pp.807-812
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• 2024

Breast lymphomas are rare, malignant breast neoplasms with a heterogeneous pattern of clinical symptoms. Burkitt's lymphoma is a rare, highly aggressive, and rapidly growing B-cell non-Hodgkin lymphoma. We report about a 27-year-old woman diagnosed as having secondary breast Burkitt's lymphoma, probably originating from the stomach, with multiple distant metastases. Breast ultrasonography revealed multiple, variable sized, heterogeneous masses with posterior acoustic enhancement and echogenic rims. These imaging findings may sometimes overlap with those of other breast malignancies. However, unlike other breast malignancies, lymphoma can be diagnosed by biopsy and does not require surgical excision. To avoid unnecessary treatment, radiologists and clinicians should be aware of the characteristic imaging features of breast lymphomas.