• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.81-84
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• 2004

In this paper, we propose a virtual sound localization algorithm which improves the sound localization accuracy and sound color preservation for two channel and multi-channel surround speaker layouts. In conventional CPP laws, the sound direction is different from the panning angle and the sound color is different from real sound source especially when the speakers are spread out widely. To overcome this drawback, we design a virtual sound localization algorithm using directional psychoacoustic criteria (DPC) and sound color compensator (SCC). The analysis results show that in the case of the proposed system, the sound direction is the same as the panning angle in the audible frequency range and the sound color is less deviated from a real sound source than the conventional CPP law. In addition, its performance is verified by means of subjective tests using a real sound source.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.142-148
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• 2011

The final aim of the present study is to develop the intelligent robot, emulating human synesthetic skills which make it possible to associate a color image with a specific sound. This can be done on the basis of the mutual conversion between color image and sound. As a first step of the final goal, this study focused on a basic system using a conversion of color image into sound. This study describes a proposed method to convert color image into sound, based on the likelihood in the physical frequency information between light and sound. The method of converting color image into sound was implemented by using HSI histograms through RGB-to-HSI color model conversion, which was done by Microsoft Visual C++ (ver. 6.0). Two different color images were used on the simulation experiments, and the results revealed that the hue, saturation and intensity elements of each input color image were converted into fundamental frequency, harmonic and octave elements of a sound, respectively. Through the proposed system, the converted sound elements were then synthesized to automatically generate a sound source with wav file format, using Csound.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.251-256
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• 2010

This paper aims for developing the intelligent robot emulating human synesthetic skills which associate a color image with sound, so that we are able to build an application system based on the principle of mutual conversion between color image and sound. As the first step, in this study, we have tried to realize a basic system using the color image to sound conversion. This study describes a new conversion method to convert color image into sound, based on the likelihood in the physical frequency information between light and sound. In addition, we present the method of converting color image into sound using color model conversion as well as histograms in the converted color model. In the basis of the method proposed in this study, we built a basic system using Microsoft Visual C++(ver. 6.0). The simulation results revealed that the hue, saturation and intensity elements of a input color image were converted into F0, harmonic and octave elements of a sound, respectively. The converted sound elements were synthesized to generate a sound source with WAV file format using Csound toolkit.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.144-148
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• 2000

A new paradigm is urgently needed to create the textile product that appeal to human Kansei or Gosei. A future of textiles depends heavily on this new paradigm. In order to create new paradigm Kansei color designs by pleasant sound are tried. These computing color designs are treated by the method of Fast fourier Transformation. As several result good color designs are given in forms of ring color patterns and band. But these judgments depend finally on human kansei. These new technology give us good hints in order to create new paradigm that appeal to Kansei goods. This new concept should be developed to higher level by additional improvements.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.101-107
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• 2012

This study describes a proposed method of converting an input sound signal into a color image by emulating human synesthetic skills which make it possible to associate an sound source with a specific color image. As a first step of sound-to-image conversion, features such as fundamental frequency(F0) and energy are extracted from an input sound source. Then, a musical scale and an octave can be calculated from F0 signals, so that scale, energy and octave can be converted into three elements of HSI model such hue, saturation and intensity, respectively. Finally, a color image with the BMP file format is created as an output of the process of the HSI-to-RGB conversion. We built a basic system on the basis of the proposed method using a standard C-programming. The simulation results revealed that output color images with the BMP file format created from input sound sources have diverse hues corresponding to the change of the F0 signals, where the hue elements have different intensities depending on octaves with the minimum frequency of 20Hz. Furthermore, output images also have various levels of chroma(or saturation) which is directly converted from the energy.

• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.231-238
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• 2012

This study aims for building an application system of converting sound into color image based on synesthetic perception. As the major features of input sound, both scale and octave elements extracted from F0(fundamental frequency) were converted into both hue and intensity elements of HSI color model, respectively. In this paper, we used the fixed saturation value as 0.5. On the basis of color model conversion theory, the HSI color model was then converted into the RGB model, so that a color image of the BMP format was finally created. In experiments, the basic system was implemented on both software and hardware(TMS320C6713 DSP) platforms based on the proposed sound-color image conversion method. The results revealed that diverse color images with different hues and intensities were created depending on scales and octaves extracted from the F0 of input sound signals. The outputs on the hardware platform were also identical to those on the software platform.

• Proceedings of the Korea Society of Design Studies Conference
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• 2003.05a
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• pp.24-25
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• 2003

• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.22-25
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• 2015

This paper performs Color Code Control Connected with Sound Source and Sensitivity of PA Speaker facility attachable LED patch. PA speaker delivers the technology to control the color code of LED patch along the present PA speakers for the facility-attached, LED the development of the patch. PA speakers facility attachable color code control technology of LED patch detects the sound from the PA speaker using a check, and if the analog signal source is detected (sound source)by converting the digital signal passes to the main controller can control the color and pattern of LED patches. In this paper, based on the PA speakers LED color control system, sound emotional linkage-type, and follow the lead of the PA speakers through the feelings can effectively channel LED linked to the source type and proceed to experiment with color and emotion control, whether or not they offer via the color control technology LED patch availability. PA speaker facility attachble color code control technology of LED patch connected with the source and future research directions in the field, and as the application is expected to be able to be widely utilized.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.11-21
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• 2021

The causes of noise generation according to the classification of indoor spaces are very diverse. Individual happiness is infringed by this noise. In this paper, We tried to visualize the spatial sound characteristics of public places using sound color to express them so that anyone can sympathize. The noise inside a conference room of a medical device company was measured for 100 minutes, and the frequency band was divided into three different types of existing sound pressure expression units. Because the size of the noise is expressed differently depending on the situation, There are cases where there is a difference of opinion between the measurer and the researcher. This noise measurement experiment was conducted, and the sound color was applied to classify it on a log scale considering auditory characteristics. As a result of comparing this with the result expression for different loudness expression units, A specific table in different units yielded almost similar results. In addition, the sound source section for 100 minutes was divided into three analysis sections, the analysis sections were different, and the size of the energy ratio for each analysis section was divided in the form of an envelope. The characteristics of the low-frequency region of the space have a high energy ratio, and the decrease in the energy ratio according to the increase in frequency is constant and regular. You can see that conversations are possible.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.427-434
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• 2016

This paper focuses on a real-time hardware processing by implementing the ARM Cortex-M4 based embedded system, using a conversion algorithm from a muscular sense to both visual and auditory elements, which recognizes rotations of a human body, directional changes and motion amounts out of human senses. As an input method of muscular sense, AHRS(Attitude Heading Reference System) was used to acquire roll, pitch and yaw values in real time. These three input values were converted into three elements of HSI color model such as intensity, hue and saturation, respectively. Final color signals were acquired by converting HSI into RGB color model. In addition, Three input values of muscular sense were converted into three elements of sound such as octave, scale and velocity, which were synthesized to give an output sound using MIDI(Musical Instrument Digital Interface). The analysis results of both output color and sound signals revealed that input signals of muscular sense were correctly converted into both color and sound in real time by the proposed conversion method.