• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.103-107
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• 2009

Because individual HRTFs (Head-Related Transfer Functions) vary from a person to a person, a HRTF database has been measured by researchers to investigate the inter-subject variation, and to generate high fidelity virtual sound image. Individual HRTFs not only vary between subjects but also vary due to wearing clothes and glasses in daily life. However, influence of different dressing condition on the measured HRTF was not sufficiently investigated. To quantify the effect of wearing clothes and glasses, dummy's HRTF is measured in an anechoic chamber with various dressing condition, and is evaluated in the sense of spectral distortion. HRTFs are measured both in the median plane and in the horizontal plane. In the median plane, under 6kHz, effect of different wearing clothes and glasses is negligible. Over 6kHz, however, effect of clothing distorts HRTF about 6dB in the sense of spectral distortion. Moreover, at high frequencies, effect of glasses is no longer negligible. In the horizontal plane, at some azimuths, even additional light cloth over the dummy can change the spectrum of HRTF (6dB spectral distortion) especially when sound source is at contralateral positions. Therefore, HRTF measurement with different wearing conditions can broaden the capability of HRTF customization whose technique utilizes a HRTF database.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.12
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• pp.1260-1268
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• 2009

Three methods(the stepped sine method, the statistical method(random excitation method) and the maximum-length sequence(MLS) method) for head-related transfer functions(HRTFs) are experimentally compared in view point of accuracy and efficiency. First, the stepped sine method has high signal-to-noise ratio, but low efficiency. Second, the statistical method is fast measurement speed, but weak to noise than the other methods. Finally, the MLS method shows both good efficiency and high signal-to-noise ratio, but it needs additional software or equipment such as MLS signal generator. For comparison of measurement accuracy, HRTFs of KEMAR dummy are measured for various azimuths and elevations. Error norms for magnitude and phase of HRTFs are defined and calculated for the measured HRTFs. The calculated error norms show that the methods give similar results in magnitude and phase except a little phase difference in the MLS method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.637-640
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• 2005

We propose a sound source localization method using the Head-Related-Transfer-Function (HRTF) to be implemented in a given platform. HRTFs contain not only the information regarding proper time delays but also phase and magnitude distortions due to diffraction and scattering by the shading object. Therefore, a set of HRTFs for any given platform provides a substantial amount of information as to the whereabouts of the source. In this study, we introduce new phase criterion in order to find the sound source location in accordance with the HRTF database empirically obtained in an anechoic chamber with the given platform. Using this criterion, we analyze the estimation performance of the proposed method in a household environment.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.16-25
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• 1997

A new method to model the HRTF's(Head-Related Transfer Function), which could give improvement of the sound localization accuracy using the spatial effects by the reflected sound wave transfer characteristics, is proposed. When using the HRTF model having reflected sound wave transfer characteristics, the accuracy of sound localization was quite improved up to about 23%, compared with using the direct wave transfer characteristics only. Furthermore, it is verified that the spatial impression could be a factor to enhance the ability of sound localization.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.663-664
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• 2009

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.706-707
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• 2014

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.338-339
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• 2009

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.04a
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• pp.201-205
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• 1998

시스템공학연구소 감성공학연구부에서는 수행중인 "멀티미디어 컨텐트용 입체음향처리 S/W개발"과제의 일환으로 머리전달함수(Head-Related Transfer Function, HRTF)의 측정을 수행하였다. 본 논문에서는 무향실에서의 HRTF 데이터 측정 과정 및 얻어진 HRTF들에 대한 음상정위청취 평가 결과에 대해 설명한다. 청취 평가에서는 피험자들이 측정된 HRTF와 MIT Media Lab의 KEMAR 더미헤드 HRTF를 사용하여 각 방향에 대해 필터링된 음원을 듣고 음상정위 주관평가를 시행하였는에, 측정된 HRTF를 사용하여 양호한 음상정위 결과를 얻을 수 있음을 확인하였다.있음을 확인하였다.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.409-415
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• 2009

The head-related transfer function (HRTF), which has an important role in virtual sound localization has different characteristics across the subjects. Measuring HRTF is very time-consuming and requires a set of specific apparatus. Accordingly, HRTF customization is often employed. In this paper, we propose a method to search an adequate HRTF from a set of the HRTFs. To achieve rapid and reliable customization of HRTF, all HRTFs in the database are partitioned, where a binary search tree was employed. The distortion measurement adopted in HRTF partitioning was determined in a heuristic way, which predicts the differences in perceived sound location well. The DC-Davis CIPIC HRTF database set was used to evaluate the effectiveness of the proposed method. In the listening test, where 10 subjects were participated, the stimuli filtered by the HRTF obtained by the proposed method were closer to those by the personalized HRTF in terms of sound localization. Moreover, performance of the proposed method was shown to be superior to the previous customization method, where the HRFT is selected by using anthropometric data.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.338-344
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• 2017

In this paper, an interpolation method of HRTF (Head-Related Transfer Function) is proposed for small-sized measurement data set, especially. The proposed algorithm is based on acoustic modeling of HRTFs, and the algorithm tries to interpolate the HRTFs via estimation the model coefficients. However, the estimation of the model coefficients is hard if there is lack of measurement points, so the algorithm solves the problem by a data augmentation using the VBAP (Vector Based Amplitude Panning). Therefore, the proposed algorithm consists of two steps, which are data augmentation step based on VBAP and model coefficients estimation step by least squares method. The proposed algorithm was evaluated by a simulation with a measured data from CIPIC (Center for Image Processing and Integrated Computing) HRTF database, and the simulation results show that the proposed algorithm reduces mean-squared error by 1.5 dB ~ 4 dB than the conventional algorithms.