• The Journal of the Acoustical Society of Korea
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• v.23 no.8
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• pp.562-569
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• 2004

An experiment for observation of the distribution of the seagrass (zostera marina) beds and characteristics of high-frequency backscattering by the photosynthesis was conducted off the coast. Acoustic data were taken as a function of the grazing angles and the relative azimuth angles on the seagrass beds of which bottom type was sandy-mud. The transmitted source signal was a 120 kHz CW waveform. Mapping of the seagrass beds distribution was drawn up using the seagrass backscattering strength with azimuth and grazing angles. The result of the comparison backscattering strength distribution of the seagrass beds was shown to be the similar to the photograph of real seagrass beds. The seagrass backscattering strength was also compared between day and night to verify the effects of the acoustical scattering by the bubbles of Photosynthetic oxygen formed on the seagrass. In these results. it is clear that observation of the seagrass beds between day and night showed the different characteristics because the bubbles of Photosynthetic oxygen affect the acoustical scattering.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.78-87
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• 2017

The goal of the present paper is to objectify the intrinsic subjectivity of sound as a media of music by applying psycho-acoustical methodology to the analysis of a musical work. First, 18 sound samples are extracted from "Symponie Fantastique" written by Hector Berlioz, which is a piece of program music, and then the objective Zwicher's sound quality parameters such as: Loudness, Sharpness, Roughness and Fluctuation Strength are evaluated for each of these sound samples. For subjective sound quality evaluation, 9 representative sound quality adjectives are extracted on a basis of program feature of Symponie Fantastique and the first jury test is carried out by using the numeric rating method and the paired comparison method. Three sound quality adjectives, "bright", "noisy", and "realistic" are extracted from the factor analysis of the first jury test result. On a basis of the computed sound metrics and the second jury test result for the three sound quality adjectives, three sound quality indexes are developed to represent the sound qualities of "Symponie Fantastique".

• The Journal of the Acoustical Society of Korea
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• v.28 no.1E
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• pp.9-15
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• 2009

In this paper, FSTL (Field Sound Transmission Loss) measured in a mock-up simulating ship cabins is studied. A mock-up is built by using 6 mm steel plate, and two identical cabins are made where 25 mm or 50 mm sandwich panel is used to construct wall and ceiling inside the steel structure. Various wall panels and ceilings are tested, where effects of wall and ceiling panel thickness, and presence of a unit toilet on FSTL are investigated. It is found that the effect of unit toilet on FSTL is at most 1 dB. From the comparison of FSTL for panels of the same thickness of 50 mm, it is observed that panel having inside air cavity of 10 mm shows higher STL than that of the panel without air cavity. Comparison of FSTL for panels of 50 mm and 25 mm thickness shows that dependency on surface density predicted by mass law is not observed. The sandwich panels act as a mass-spring system, which shows a resonant mode that cannot be explained by the mass law. It is also found that STL from laboratory test is higher than FSTL by 5- 10 dB, which can be explained by flanking structure-borne noise transmission path such as ceiling, floor and corridor-facing wall.

• Journal of KSNVE
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• v.6 no.2
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• pp.225-231
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• 1996

A free field method using two microphones is used for measuring surface impedance and absorption coefficient of the absorbent materials. It is shown that this method can be performed in a large non-anechoic room. Precise values of the surface impedance can be obtained by changing the spaces between the two microphones. Comparison between experimental values of the surface impedance of the glass wool and the mineral wool and Miki's empirical model shows agreement.

• The Journal of the Acoustical Society of Korea
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• v.31 no.3
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• pp.197-204
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• 2012

In this thesis, studied the method to minimize the changes in frequency response and level due to the variation of the distance from the source to the microphone. selecting three microphones (omni directional, cardioid, super cardioid) which are being used generally, frequency responses were measured in accordance with the distance changes. Gotten the difference from the reference as the result of measurement, changed responses for each frequency range were compensated in comparison of the original human vocal source. In low frequency range, the low frequency boost caused by the proximity effect and decrease in accordance with the distance were compensated. The variation in mid-frequency range is comparatively small, however since the mid-range is the most important part of the human vocal signal, were compensated the mid-frequency range in comparison of the reference. The human vocal signal variation in high frequency range is extremely small and the high frequency is compensated close to the original source without difficulty. Understanding the microphone characteristics and compensations, this study showed that the response can be maintain among the change of the distance from the source to the microphone.

• The Journal of the Acoustical Society of Korea
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• v.32 no.4
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• pp.329-334
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• 2013

Order spectrum analysis is widely used to grasp the features of noises due to powertrain system including engine and intake/exhaust system. It is known from many previous researches that order components related to the first and second firing frequencies of engine considerably affect the noise of car interior. The purpose of this paper is to find out the difference in sound quality: Pleasantness of car interior noise according to the change of its order spectrum. For this, car interior noises of 6-cylinder and 4-cylinder engines are recorded and their order spectrum levels are modified by applying adaptive digital filters. After subjective listening test employing paired comparison method is conducted, it is investigated that the level change of half-order components is a noticeable factor to improve Pleasantness of the car interior noises whereas level decrease of firing order does not always give the positive effect on its sound quality.

• The Journal of the Acoustical Society of Korea
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• v.13 no.6
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• pp.5-14
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• 1994

This paper is about an experiment of speaker-independent automatic Korean spoken words recognition using Multi-Layered Perceptron and Error Back-propagation algorithm. The object words are 50 citynames of D.D.D local numbers. 43 of those are 2 syllables and the rest 7 are 3 syllables. The words were not segmented into syllables or phonemes, and some feature components extracted from the words in equal gap were applied to the neural network. That led independent result on the speech duration, and the PARCOR coefficients calculated from the frames using linear predictive analysis were employed as feature components. This paper tried to find out the optimum conditions through 4 differerent experiments which are comparison between total and pre-classified training, dependency of recognition rate on the number of frames and PAROCR order, recognition change due to the number of neurons in the hidden layer, and the comparison of the output pattern composition method of output neurons. As a result, the recognition rate of $89.6\%$ is obtaimed through the research.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.454-460
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• 2020

Artificial intelligence assistants that provide speech recognition operate through cloud-based voice recognition with high accuracy. In cloud-based speech recognition, Wake-Up-Word (WUW) detection plays an important role in activating devices on standby. In this paper, we compare the performance of Convolutional Neural Network (CNN)-based WUW detection models for mobile devices by using Google's speech commands dataset, using the spectrogram and mel-frequency cepstral coefficient features as inputs. The CNN models used in this paper are multi-layer perceptron, general convolutional neural network, VGG16, VGG19, ResNet50, ResNet101, ResNet152, MobileNet. We also propose network that reduces the model size to 1/25 while maintaining the performance of MobileNet is also proposed.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.10-15
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• 2001

In this paper, we describe the comparison between the combination of features using a speech and music discrimination, which is classifying between speech and music on audio signals. Audio signals are classified into 3classes (speech, music, speech and music) and 2classes (speech, music). Experiments carried out on three types of feature, Mel-cepstrum, energy, zero-crossings, and try to find a best combination between features to speech and music discrimination. We using a Gaussian Mixture Model (GMM) for discrimination algorithm and combine different features into a single vector prior to modeling the data with a GMM. In 3classes, the best result is achieved using Mel-cepstrum, energy and zero-crossings in a single feature vector (speech: 95.1％, music: 61.9％, speech & music: 55.5％). In 2classes, the best result is achieved using Mel-cepstrum, energy and Mel-cepstrum, energy, zero-crossings in a single feature vector (speech: 98.9％, music: 100％).

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.568-573
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• 2019

In the diagnosis of pulmonary diseases, auscultation technique is simpler than the other methods, and lung sounds can be used for predicting the types of pulmonary diseases as well as identifying patients with pulmonary diseases. Therefore, in this paper, we identify patients with pulmonary diseases and classify lung sounds according to their sound characteristics using various convolutional neural networks, and compare the classification performance of each neural network method. First, lung sounds over affected areas of the chest with pulmonary diseases are collected by using a single-channel lung sound recording device, and spectral features are extracted from the collected sounds in time domain and applied to each neural network. As classification methods, we use general, parallel, and residual convolutional neural network, and compare lung sound classification performance of each neural network through experiments.