• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.1009-1009
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• 2003

VIPER a new tool for the VIsual PERception of sound quality and for sound design will be presented. Requirement for the visualization of sound quality is a signal analysis modeling the information processing of the ear. The first step of the signal processing implemented in VIPER, calculates an auditory spectrogram by a filter bank adapted to the time- and frequency resolution of the human ear. The second step removes redundant information by extracting time- and frequency contours from the auditory spectrogram in analogy to contours of the visual system. In a third step contours and/or auditory spectrogram can be resynthesised confirming that only aurally relevant information were extracted. The visualization of the contours in VIPER allows intuitively to grasp the important components of a signal. Contributions of parts of a signal to the overall quality can be easily auralized by editing and resynthesising the contours or the underlying auditory spectrogram. Resynthesis of time contours alone allows e.g. to auralize impulsive components separately from the tonal components. Further processing of the contours determines tonal parts in form of tracks. Audible differences between two versions of a sound can be visually inspected in VIPER through the help of auditory distance spectrograms. Applications are shown for the sound design of several interior noises of cars.

• Journal of KSNVE
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• v.6 no.4
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• pp.499-502
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• 1996

Interior noise, engine speed and vehicle speed are measured under transient road-load condition and interior noise signal is transformed by using the transient signal analysis methods, such as the spectrogram and wavelet transform. Using the analyzed results, subjective noise metrics such as the loudness, sharpness and articulation index at each vehicle speed can be estimated and characteristics of interior noise for various running modes can be discussed in the viewpoint of noise quality.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.2
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• pp.115-124
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• 2015

A methodology is proposed to estimate a trajectory of a flying target and its velocity using the time and frequency analysis of the acoustic signal. The measurement of sound emitted from a flying acoustic source with a microphone above a ground shall receive both direct and ground-reflected sound waves. For certain frequency contents, the destructive interference happens in received signal waveform reflected path lengths are in multiple integers of direct path length. This phenomenon is referred to as the acoustical mirror effect and it can be observed in a spectrogram plot. The spectrogram of acoustic measurement for a flying vehicle measurement shows several orders of destructive interference curves. The first or second order of curve is used to find the best approximate path by using nonlinear least-square method. Simulated acoustic signal is generated for the condition of known geometric of a sensor and a source in flight. The estimation based on cepstrogram analysis provides more accurate estimate than spectrogram.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.19 no.2
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• pp.101-106
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• 2008

The speech signal has been put into a form suitable for storage and analysis by computer, several different operation can be performed. Filtering, sampling and quantization are the basic operation in digiting a speech signal. The waveform can be displayed, measured and even edited, and spectra can be computed using methods such as the Fast Fourier Transform (FFT), Linear predictive Coding (LPC), Cepstrum and filtering. The digitized signal also can be used to generate spectrograms. The spectrograph provide major advantages to the study of speech. So, author introduces the basic techniques for the acoustic recording, digital signal processing and the principles of spectrum and spectrogram.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.1
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• pp.43-47
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• 2016

This system is a diagnosis system that checks whether it causes a partial discharge of a power cable or not. It is to classify normal from abnormal-normal, PD (Partial Discharge) sound through analysis of RLCR (Relative Level Crossing Rate) and spectrogram energy algorithm. Partial discharge diagnostic system has a function that stores PD sound and analyzes the data. The wave shape of PD sound is similar to noise and is systematically generated by partial discharge. Therefore, in this paper, we could discreminate between normal and abnormal case using relative level crossing rate (RLCR) and spectrogram of frequency energy rate.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.801-804
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• 2001

This article is concerned with automatic segmentation of two adjacent vowels for speech signals. All kinds of transition case of adjacent vowels can be characterized by spectrogram. Firstly the voiced-speech is extracted by the histogram analysis of vowel indicator which consists of wavelet low pass components. Secondly given phonetic transcription and transition pattern spectrogram, the voiced-speech portion which has consecutive vowels automatically segmented by the template matching. The cross-correlation function is adapted as a template matching method and the modified correlation coefficient is calculated for all frames. The largest value on the modified correlation coefficient series indicates the boundary of two consecutive vowel sounds. The experiment is performed for 154 vowel transition sets. The 154 spectrogram templates are gathered from 154 words(PRW Speech DB) and the 161 test words(PBW Speech DB) which are uttered by 5 speakers were tested. The experimental result shows the validity of the method.

• Journal of Sasang Constitutional Medicine
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• v.8 no.2
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• pp.191-202
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• 1996

Sasang constitution classification is very important subject, so many medical men studied the Sasang constitution classification but there is no certain method to classify objectively. And the purpose of this study is to help classifying Sasang constitution through correlation with sound spectrogram. This study was done it under the suppose that Sasang costitution hag correlation with sound spectrogram. The following results were obtained about correlation between sound spectrogram and Sasang constitution by comparison and analysis the pitch and reading speed of Sasang constitutions; 1. There was a similar tendency in the composition reading speed between taeeumin, soeumin and soyangin. 2. Taeeumin's center was lower measured more than soeumin's and soyangin's in the pitch graph and graph by normal curve fit and there was a similar tendency between soeumin and soyangin. 3. There was a similar tendency in the pitch graph's width between all constitutions. 4. There was a significant difference between taeeumin and soeum in the mean of three constitution's pitch, this means that taeeumin uses lower voice more than soeumin. According to the results, it is considered that there is a correlation between pitch of sound spectrogram and Sasang constitution. And method of Sasang constitution classification through sound spectrogram analysis can be one method as assistant for the objectification of Sasang constitution classification.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.28 no.2
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• pp.100-105
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• 2017

Background and Objectives : Adductor type spasmodic dysphonia (ADSD) is neurogenic disorder and focal laryngeal dystonia, while muscle tension dysphonia (MTD) is caused by functional voice disorder. Both ADSD and MTD may be associated with excessive supraglottic contraction and compensation, resulting in a strained voice quality with spastic voice breaks. The aim of this study was to determine the utility of spectrogram analysis in the differentiation of ADSD from MTD. Materials and Methods : From 2015 through 2017, 17 patients of ADSD and 20 of MTD, underwent acoustic recording and phonatory function studies, were enrolled. Jitter (frequency perturbation), Shimmer (amplitude perturbation) were obtained using MDVP (Multi-dimensional Voice Program) and GRBAS scale was used for perceptual evaluation. The two speech therapist evaluated a wide band (11,250 Hz) spectrogram by blind test using 4 scales (0-3 point) for four spectral findings, abrupt voice breaks, irregular wide spaced vertical striations, well defined formants and high frequency spectral noise. Results : Jitter, Shimmer and GRBAS were not found different between two groups with no significant correlation (p>0.05). Abrupt voice breaks and irregular wide spaced vertical striations of ADSD were significantly higher than those of MTD with strong correlation (p<0.01). High frequency spectral noise of MTD were higher than those of ADSD with strong correlation (p<0.01). Well defined formants were not found different between two groups. Conclusion : The wide band spectrograms provided visual perceptual information can differentiate ADSD from MTD. Spectrogram analysis is a useful diagnostic tool for differentiating ADSD from MTD where perceptual analysis and clinical evaluation alone are insufficient.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.2110-2116
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• 2009

The culture industry very have interested in modern society so that it is a field to be provided opportunity to can benefits of life with health, medical industry. Especially, music industry to have based on popular support has acknowledged as artistic value to can easily approach that expresses a feeling to exist together with popularity, originality. In this paper, we will want to design indicators to evaluate a singer's musical talent to can speak a key part in these music industry. From this, we applied analysis elements of spectrogram to perform in change of vocal tract shape in singer's voice and public voice about identical music, and performed comparison, analysis of two groups to experiment pattern analysis of result waveform. Therefore, we analyzed pattern in change of vocal tract shape choice a popular music using of experiment to collect singer and public voice about identical part with time so that we designed indicator to can evaluate musicality.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.977-985
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• 2016

In this paper, we propose a new method for on-line genre classification using spectrogram and deep neural network. For on-line processing, the proposed method inputs an audio signal for a time period of 1sec and classifies its genre among 3 genres of speech, music, and effect. In order to provide the generality of processing, it uses the spectrogram as a feature vector, instead of MFCC which has been widely used for audio analysis. We measure the performance of genre classification using real TV audio signals, and confirm that the proposed method has better performance than the conventional method for all genres. In particular, it decreases the rate of classification error between music and effect, which often occurs in the conventional method.