• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.557-565
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• 2009

To perceive the direction and the distance of a sound, we always use a couple of information. Head Related Transfer Function (HRTF) contains the information that sound arrives from a sound source to the ears of the listener, like differences of level, phase and frequency spectrum. For a reproduction system using 2 channels, we apply HRTF to many algorithms which make 3d sound. But it causes a problem to localize a sound source around a certain places which is called the cone-of-confusion. In this paper, we proposed the new algorithm to reduce the confusion of sound image localization. The difference of frequency spectrum and psychoacoustics theory are used to boost the spectral cue among each directions. To confirm the performance of the algorithm, informal listening tests are carried out. As a result, we can make the improved 3d sound in 2 channel system based on a headphone. Also sound quality of improved 3d sound is much better than conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.27 no.4
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• pp.207-214
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• 2008

To create 3D sound, we usually use two methods which are two channels or multichannel sound systems. Because of cost and space problems, we prefer two channel sound system to multi-channel. Using a headphone or two speakers, the most typical method to create 3D sound effects is a technology of head related transfer function (HRTF) which contains the information that sound arrives from a sound source to the ears of the listener. But it causes a problem to localize a sound source around a certain places which is called cone-of-confusion. In this paper, we proposed the new algorithm to reduce the confusion of sound image localization. HRTF grouping and psychoacoustics theory are used to boost the spectral cue with spectrum difference among each directions. Informal listening tests show that the proposed method improves the front-back sound localization characteristics much better than conventional methods.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.448-457
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• 2006

HRTF DB, including the information of the sounds which is arrived to our ears, is generally used to make a 3D sound. But it can decline some three-dimensional effects by the confusion between front and back directions due to the non-individual HRTF depending on each listener. In this paper, we propose a new method to use psychoacoustic theory that reduces the confusion of sound image localization. And we make use of an excitation energy by the sense of hearing. This method is brought HRTF spectrum characteristics into relief to draw out the energy ratio about the bark band. Informal listening tests show that the proposed method improves the front-back sound localization characteristics much better than the conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.30 no.4
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• pp.181-189
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• 2011

According to developments of digital signal processing, 3D sound come into focus on multimedia systems. Many studies on 3d sound have proposed lots of clues to create realistic sounds. But these clues are only focused on binaural systems which two ears are normal. If we make the 3d sound using those clues at monaural systems, the performance goes down dramatically. In order to use the clues for monaural systems, we have studies algorithms such as duplex theory. In duplex theory, the sounds that we listen are affected by human's body, pinna and shoulder. So, we can enhance sound localization performances using its characteristics. In this paper, we propose a new method to use psychoacoustic theory that creates realistic 3D audio at monaural systems. To improve 3d sound, we calculate the excitation energy rates of each symmetric HRTF and extract the weights in each bark range. Finally, they are applied to emphasize the characteristics related to each direction. Informal listening tests show that the proposed method improves sound localization performances much better than the conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.29 no.4
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• pp.270-277
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• 2010

In this paper, we proposed an algorithm that improves tone quality of noisy audio signals by using ICA(Independent Component Analysis) algorithm and perceptual filters. Many algorithms have been proposed to eliminate the noise from the audio signals, such as spectral subtraction method, perceptual filter, etc. The perceptual filter uses a noise that is acquired from silent ranges in the input signal. In this case, the improvement rate of tone quality decreases if the noise energy is changed by the environmental variation in a signal frame. But the proposed method estimates a noise that is changed at each frame using ICA algorithm. The estimated noise is applied to perceptual filter. To show the performance of the proposed algorithm, several tests are performed to various input signals. With the proposed algorithm, we could confirm the enhancement of tone quality in terms of segmental SNR (SSNR), noise-to-mask ratio (NMR) and Degradation Category Rating (DCR) test.