• Proceedings of the ESK Conference
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• 1995.04a
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• pp.35-39
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• 1995

인간의 감성평가 기술은 제품설계에 필요한 중요한 기술로 인식되고있다. 정량적이고 객 관적인 감성평가를 위한 구체적인 연구가 요구된다. 본 연구는 생리신호가 인간감성에 따라 변화한 다는 가정아래 인간 오감(청각, 시각, 후각, 미각, 촉각)에 대한 생리신호 (EEG, ECG, GSR, FEMG)의 변화를 측정하였다. 감각종류로 긍정적 감성과 부정적 감성을 유발할 4개의 자극이 피실험자에게 제시되었고, 모든 생리신호를 동기화하여 측정하였다. 측정된 신호는 통계처리하여 주관적으로 평가한 감성과의 상관성을 분석하였고 긍정적인 감성과 부정적인 감성에 따른 신호변화의 특성을 파악하여 감 성평가를 위한 상관성을 관찰했다.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.600-605
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• 2020

In this paper, we propose a sound event detection method using a multi-channel multi-scale neural networks for sound sensing home monitoring for the hearing impaired. In the proposed system, two channels with high signal quality are selected from several wireless microphone sensors in home. The three features (time difference of arrival, pitch range, and outputs obtained by applying multi-scale convolutional neural network to log mel spectrogram) extracted from the sensor signals are applied to a classifier based on a bidirectional gated recurrent neural network to further improve the performance of sound event detection. The detected sound event result is converted into text along with the sensor position of the selected channel and provided to the hearing impaired. The experimental results show that the sound event detection method of the proposed system is superior to the existing method and can effectively deliver sound information to the hearing impaired.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.687-693
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• 2003

In this paper, a new adaptive audio signal enhancement algorithm is proposed. In order to remove a broadband noise from a noisy signal, a filter is designed and applied adaptively to noisy audio signal. The noisy signal is first transformed to frequency domain and divided into bark domain to calculate excitation energy. A filter will be calculated to eliminate the noise by using the excitation energy and noisy energy which is obtained from a silent area. The filter is adaptively adjusted and continuously applied until the threshold point is met. The algorithm also works well even though the noise's energy change all of a sudden. SNR, NMR comparison and MOS Test are performed to show the effectiveness of the proposed algorithm.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.199-202
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• 2002

본 논문에서는 사람의 청각 모델을 기반으로 잡음에 의해 손상된 음성 신호로부터 잡음 신호의 마스킹 특성과 신호에너지의 지각(知覺)을 나타내는 임계대역(critical band)에서의 잡음 에너지에 대한 지각 패턴인 noise excitation pattern을 이용한 잡음 에너지 차감과 잡음 추정 오차에 의한 변형된 음성신호 내의 순음(tonal) 성분과 비순음(non-tonal)성분의 보정을 통해 효과적인 음성 품질의 개선을 위한 연구를 하였다.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.36 no.4
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• pp.314-321
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• 2000

In order to obtain the fundamental data on the auditory thresholds of fishes for catching method using low frequency sound, the auditory thresholds of coralfish Chromis notatus were measured in the presence of masking noise in the spectrum level range of 73~83dB re l$\mu$Pa/√Hz by heartbeat conditioning technique using pure tones coupled with a delayed electric shock. Critical ratios were about 23~41dB at measurement frequency, The critical ratio increased almost linearly with increasing frequency from 500Hz. The noise spectrum level at the start of masking was about 60~65dB. This suggests that hearing of coralfish is masked in the natural environment with the noise spectrum level above 60dB. The sound pressure level of which the signal sound of 300Hz is recognized by coralfish under the ambient noise is above 88dB and the critical ratio of them is above 23dB. The hearing index of coralfish with ambient noise was 81.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.181-187
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• 2013

When there are background noises or some people speaking at the same time, a human's auditory sense has the ability to listen the target speech signal with a specific purpose through Auditory Scene Analysis. The CASA system with human's auditory faculty system is able to segregate the speech. However, the performance of CASA system is reduced when the CASA system fails to determine the correct position of the speech. In order to correct the error in locating the speech on the CASA system, voice activity detection algorithm is proposed in this paper, which is a combined auditory scene analysis with PAR(Periodic to Aperiodic component Ratio). The experiments have been conducted to evaluate the performance of voice activity detection in environments of white noise and car noise with the change of SNR 15~0dB. In this paper, by comparing the existing algorithms (Pitch and Guoning Hu) with the proposed algorithm, the accuracy of the voice activity detection performance has been improved as the following: improvement of maximum 4% at SNR 15dB and maximum 34% at SNR 0dB for white noise and car noise, respectively.

• Journal of Biomedical Engineering Research
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• v.23 no.3
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• pp.227-233
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• 2002

The IME(implantable middle ear) system is Promising due to its ability to free from sound feedback and Produce a good sound quality and intelligibility with low distortion even if it is operated with high gain for severe hearing impaired. The differential electromagnetic vibration transducer. which was developed for using in IME system and has two small magnets attached the same Pole facing in the coil. is not influenced by environmental external magnetic field. Besides, it has high vibration efficiency and good frequency response characteristics. In this Paper, using acoustic model of the transducer and ear model of normal Person. the signal transfer characteristics of the IME system are analyzed and investigated From the differences of the characteristics between normal ear and the IME system, it is Possible that design of the IME system that have the signal transfer characteristics similar to normal person's ear.

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.237-244
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• 1994

We investigated the qualitive and quantitative properties in EEG signal which responds to auditory stimulus with increaing the sound-cutting frequency from 2 Hz to 20 Hz by 2 Hz step units, by chaotic dynamics. To bigin with, general chaotic properties such as fractal mechanism, 1 If frequency spectrum and positive Lyapunov exponent are discussed in EEG signal. For evoked potential with given auditory stimulus, the route to chaos by bifurcation diagram and the changes in geometrical property of Poincare sections of 2-dimensional psedophase space is observed. For that containing spontaneous potential, seen as the random background signal, the chaotic attractors in 3-dimensional phase space are found containing the same infomation as the above mentioned evoked potential. Finally the chinges of Lyapunov exponent by various sound-cutting frequencies of stimulus and by the various spatial positions (occipital region) in a brain surface to be measured, are illustrated meaningfully.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.115-121
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• 2022

In this paper, we propose a music classification system according to user emotions using Electroencephalogram (EEG) features that appear when listening to music. In the proposed system, the relationship between the emotional EEG features extracted from EEG signals and the auditory features extracted from music signals is learned through a deep regression neural network. The proposed system based on the regression model automatically generates EEG features mapped to the auditory characteristics of the input music, and automatically classifies music by applying these features to an attention-based deep neural network. The experimental results suggest the music classification accuracy of the proposed automatic music classification framework.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.968-970
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• 2022

일반적으로 가정 내에서 발생하는 안전 사고의 비율은 비장애인에 비해 청각장애인이 높다. 이는 외부인에게 도움을 받을 수 없는 상황에서 청각장애인 스스로 위험상황에 대한 소리를 인지하지 못하기 때문이다[1]. 본 연구에서는 이러한 문제를 해결하기 위해 시각적 효과 또는 진동 신호를 통해 청각장애인들에게 사고 상황 인지를 돕는 시스템을 제안한다. 현재 상용 제품의 경우는 청각장애인이 스마트기기를 소지하고 있을 때만 알림을 인지할 수 있기 때문에 긴급 상황에서 효과가 떨어질 수 있다. 따라서 제안 시스템에서는 어플리케이션 알림과 함께 건물내 전등 색상에 변화를 주는 서비스를 개발하여 스마트 기기를 소지하지 않는 상황에서도 위험상황에 대한 즉각적인 인지를 통해 위험에 대처할 수 있도록 한다. 소리를 시각화하는 것이 본 연구의 핵심 방법론이며 이를 위해 Convolutional Neural Network 모델과 라즈베리파이를 활용하였다.