• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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• pp.3-8
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• 1992

The theory of subjective preference with temporal and spatial factors which include sound signals arriving at both ears is described. Then, auditory evoked potentials which may relate to a primitive subjective response namely subjective preference are discussed. According to such fundamental phenomena, a workable model of human auditory-brain system is proposed. For eample, important subjective attributes, such as loudness, coloration, threshold of preception of a reflection and echo distrubance as well as subjective preference in relation to the initial time delay gap between the direct sound and the first reflection, and the subsequent reverberation time are well described by the autocorrelation function of source signals. Speech clarity, subjective diffuseness as well as subjective preference are related to the magnitude of inter-aural crosscorrelation function (IACC). Even the caktail party effects may be eplained by spatialization of human brain, i.e., independence of temporal and spatial factors.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.329-332
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• 1999

Currently, the most important technology is compression methods in the multimedia society. In audio compression, the method using human auditory nervous property is used. This method using psychoacoustical model is applied to perceptual audio coding, because human's audibility is limited. MPEG-II AAC(Advanced Audio Coding) is the most advanced coding scheme that is of benefit to high quality audio coding. The compression ratio is 1.4 times compared with MPEG-I layer-III. In this paper, the vector processor for MDCT/IMDCT(Modified Discrete Cosine Transform /Inverse Modified Discrete Cosine Transform) of MPEG-II AAC is designed.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.209-214
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• 2013

Improve the recognition performance of speech recognition systems as a method for recognizing human listening skills were incorporated into the system. In noisy environments by separating the speech signal and noise, select the desired speech signal. but In terms of practical performance of speech recognition systems are factors. According to recognized environmental changes due to noise speech detection is not accurate and learning model does not match. In this paper, to improve the speech recognition feature extraction using gamma tone and learning model using acoustic model was proposed. The proposed method the feature extraction using auditory scene analysis for human auditory perception was reflected In the process of learning models for recognition. For performance evaluation in noisy environments, -10dB, -5dB noise in the signal was performed to remove 3.12dB, 2.04dB SNR improvement in performance was confirmed.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.2 no.1
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• pp.27-33
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• 2009

Generally, implantable microphone has been implanted in the temporal bone for implantable middle ear hearing devices (IMEHDs). In this case, the microphone's membrane can be damaged and can be generated biological noise. In order to overcome the these problems, the location of implanted microphone should be changed. As an alternative, the microphone can be implanted in the external auditory canal. However, the sound emission can be produced because of vibration transducer toward reverse direction from the tympanic membrane to the external auditory canal. In this paper, an amount of the emitted sound is measured using a probe microphone as the changing the position of microphone in the external auditory canal of a physical ear model, which is similar to acoustical and vibratory properties of the human ear. Through the measured value, the location of the microphone was assumed in the external auditory canal. According to the analysis, the microphone input sound can be decreased when microphone position become more distance from the tympanic membrane in the auditory canal. However, the external auditory canal is not appropriated to implantable microphone position, because sound emission is not completely eliminated.

• Journal of IKEEE
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• v.22 no.2
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• pp.362-368
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• 2018

This paper has implemented a mutual conversion system that mutually converts between body motion signals and both visual and auditory signals. The present study is based on intentional synesthesia that can be perceived by learning. The Euler's angle was used in body movements as the output of a wearable armband(Myo). As a muscle sense, roll, pitch and yaw signals were used in this study. As visual and auditory signals, MIDI(Musical Instrument Digital Interface) signals and HSI(Hue, Saturation, Intensity) color model were used respectively. The method of mutual conversion between body motion signals and both visual and auditory signals made it easy to infer by applying one-to-one correspondence. Simulation results showed that input motion signals were compared with output simulation ones using ROS(Root Operation System) and Gazebo which is a 3D simulation tool, to enable the mutual conversion between body motion information and both visual and auditory information.

• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.162-167
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• 2012

This paper proposes a speech processing system based on a model of the human auditory system and a noise reduction neural network with fast Fourier transform (FFT) amplitude and phase spectrums for noise reduction under background noise environments. The proposed system reduces noise signals by using the proposed neural network based on FFT amplitude spectrums and phase spectrums, then implements auditory processing frame by frame after detecting voiced and transitional sections for each frame. The results of the proposed system are compared with the results of a conventional spectral subtraction method and minimum mean-square error log-spectral amplitude estimator at different noise levels. The effectiveness of the proposed system is experimentally confirmed based on measuring the signal-to-noise ratio (SNR). In this experiment, the maximal improvement in the output SNR values with the proposed method is approximately 11.5 dB better for car noise, and 11.0 dB better for street noise, when compared with a conventional spectral subtraction method.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.369-376
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• 2004

The tinnitus retraining therapy(TRT) is an effective method for treating tinnitus patients. This therapy use the white noise to stimulate auditory cells for a wide frequency range. In this paper, the small white noise generator using the thermal noise is proposed. And frequency response controller which can compensate the frequency response changed by the human outer and middle ear system is proposed. We can know that proposed system is more proper type on a purpose of the tinnitus retraining therapy comparing with conventional white noise generator.

• Journal of the Ergonomics Society of Korea
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• v.16 no.1
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• pp.85-96
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• 1997

This article reviews the effects of VDT tasks on multiple resources for processing and storage in short-term working memory. MD and PD method were introduced toevaluate the modalities (auditory-visual) in the multiple resources model. The subjects conducted 2 sessions of 50 minites VDT tasks. Before, between and after VDT tasks, MD, PD task performance scores and CFF(critical flicker frequency0 values were measured. The review suggested that the modalities of human information processing in working memory were affected by VDT tasks with different task contents.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.872-875
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• 2002

A digital watermarking technique applying psychoacoustic model for audio signal is proposed in this paper. In the watermarking scheme, the pseudo-random bit stream used as a watermark signal is embedded into the audio signal in both speech and music. The strength of the embedded signal is subject to the human auditory system in such a way that the disturbances on host audio signal are beyond the sensing of human ears. The experimental results show that the quality of the watermarked audio signal, in term of signal to noise ratio, can be improved up to 3.2 dB.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.735-742
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• 2019

In this paper, we propose a method of extracting speech features for phoneme recognition based on spikegram. The Fourier-transform-based features are widely used in phoneme recognition, but they are not extracted in a biologically plausible way and cannot have high temporal resolution due to the frame-based operation. For better phoneme recognition, therefore, it is desirable to have a new method of extracting speech features, which analyzes speech signal in high temporal resolution following the model of human auditory system. In this paper, we analyze speech signal based on a spikegram that models feature extraction and transmission in auditory system, and then propose a method of feature extraction from the spikegram for phoneme recognition. We evaluate the performance of proposed features by using a DNN-based phoneme recognizer and confirm that the proposed features provide better performance than the Fourier-transform-based features for short-length phonemes. From this result, we can verify the feasibility of new speech features extracted based on auditory model for phoneme recognition.