• Phonetics and Speech Sciences
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• v.10 no.4
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• pp.163-171
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• 2018

A mixed dysarthria with combinations of hypokinetic, ataxic, and spastic components is a common clinical feature of multiple system atrophy (MSA). Due to the rapid progress of dysarthria after diagnosis, people with MSA experience difficulty with verbal communication, which eventually affects their quality of life negatively. In this study, SPEAK $OUT!^{(R)}$, an intensive 1:1 treatment of dysarthria for improving functional communicative ability, was provided to twelve people with MSA. To evaluate the efficacy of SPEAK $OUT!^{(R)}$ in people with MSA, aerodynamic, acoustic, and perceptual analyses were conducted. Pre-and post-therapy data included maximum phonation time, vocal intensity, and fundamental frequency during /a/ sustained phonation and passage reading; frequency range between high /a/ and low /a/ phonation; jitter, shimmer, and HNR for vocal quality; speech rate during passage reading; and perceptual evaluation scores for articulation precision and intonation. The participants achieved statistically significant improvement in vocal intensity, pitch range, vocal quality, speech rate, and speech intelligibility. In conclusion, SPEAK $OUT!^{(R)}$ is a feasible treatment for people with MSA to efficaciously improve their speech ability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2230-2250
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• 2015

Multiple projectors with partially overlapping regions can be used to project a seamless image on a large projection surface. With the advent of high-resolution photography, such systems are gaining popularity. Experts set up such projection systems by subjectively identifying the types of errors induced by the system in the projected images and rectifying them by optimizing (correcting) the parameters associated with the system. This requires substantial time and effort, thus making it difficult to set up such systems. Moreover, comparing the performance of different multi-projector display (MPD) systems becomes difficult because of the subjective nature of evaluation. In this work, we present a framework to quantitatively determine the quality of an MPD system and any image projected using such a system. We have divided the quality assessment into geometric and photometric qualities. For geometric quality assessment, we use Feature Similarity Index (FSIM) and distance-based Scale Invariant Feature Transform (SIFT). For photometric quality assessment, we propose to use a measure incorporating Spectral Angle Mapper (SAM), Intensity Magnitude Ratio (IMR) and Perceptual Color Difference (ΔE). We have tested the proposed framework and demonstrated that it provides an acceptable method for both quantitative evaluation of MPD systems and estimation of the perceptual quality of any image projected by them.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.125-128
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• 2000

In this paper, we proposed the high quality digital audio watermarking algorithm in the frequency domain. The spread spectrum technique is used to encrypted a stream of information by spreading the data as much of the frequency spectrum as possible. It's technique adapt well to data hiding in audio signal. We have used the perceptual model and MDCT/IMDCT for the high qualify digital audio watermarking. The proposed watermark algorithm preserved high quality audio data from watermark signal.

• Journal of Korean Society for Quality Management
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• v.26 no.3
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• pp.1-16
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• 1998

Even though advocates of TQM emphasize the role of TQM more than before, the interest of the public at large have decreased in recent years. In order to explain the perceptual gap between the advocates and general public, three questions were considered: 1) Is TQM a dying fad\ulcorner 2) Does TQM focus on a particular facet of management\ulcorner 3) Does TQM pursue incremental improvement, while reengineering pursue breakthrough innovation\ulcorner It is also discussed how can we extend the horizon of TQM so as to integrate new management theories into the framework of TQM.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.127-133
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• 2009

With advances in video technology, many researchers are interested in video quality assessment to prove better performance of proposed algorithms. Since human visual system is too complex to be formulated exactly, many researches about video quality assessment are in progressing. No-reference video-quality assessment is suitable for various video streaming services, because of no requested additional data and network capacity to perform quality assessment. In this paper, we propose a novel no-reference video-quality assessment method with the estimation of dynamic range distortion. To measure the performance, we obtain mean opinion score (MOS) data by subject video quality test with the ITU-T P.910 Absolute Category Rating (ACR) method. And, we compare it with proposed algorithm using 363 video sequences. Experimental results show that the proposed algorithm has a higher correlation with obtained MOS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3823-3840
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• 2020

Recently, auto-encoder has emerged as the most popular method in convolutional neural network (CNN) based image compression and has achieved impressive performance. In the traditional auto-encoder based image compression model, the encoder simply sends the features of last layer to the decoder, which cannot allocate bits over different spatial regions in an efficient way. Besides, these methods do not fully exploit the contextual information under different receptive fields for better reconstruction performance. In this paper, to solve these issues, a novel auto-encoder model is designed for image compression, which can effectively transmit the hierarchical features of the encoder to the decoder. Specifically, we first propose an adaptive bit-allocation strategy, which can adaptively select an importance channel. Then, we conduct the multiply operation on the generated importance mask and the features of the last layer in our proposed encoder to achieve efficient bit allocation. Moreover, we present an additional novel perceptual loss function for more accurate image details. Extensive experiments demonstrated that the proposed model can achieve significant superiority compared with JPEG and JPEG2000 both in both subjective and objective quality. Besides, our model shows better performance than the state-of-the-art convolutional neural network (CNN)-based image compression methods in terms of PSNR.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.203-205
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• 2014

본 논문에서는 HEVC 기반 비디오 부호화에 있어 CTU 단위의 시각 민감도에 따라 CTU 별로 QP 를 조절하여 주관적 화질을 향상시키는 방법을 제안한다. 시각 민감도를 측정하는 방법으로서 화소 영역에서의 최소가지차(JND, just noticeable distortion)를 계산하여 이용하였고, 이를 HM 12.0 참조 소프트웨어에서 이용되는 $R-{\lambda}$ 모델 기반의 율 제어 모듈에 결합하여 시각 민감도에 따라 QP 를 제어할 수 있도록 하였다. 시각 민감도가 큰 영상의 영역에 대해서는 상대적으로 작은 QP 값을, 시각민감도가 작은 영역에 대해서는 큰 QP 값을 양자화 과정에 적용함으로써, 시각 민감도가 작은 영역에 대해서는 사용 비트양을 절약하고, 절약된 비트를 상대적으로 시각 민감도가 큰 영역을 위해 사용함으로써 비디오의 주관적 화질을 향상시킬 수 있었다. 뿐만 아니라 이를 하드웨어에 적용 가능하게 하기 위해 HM 12.0 기반 하드웨어 구현을 위한 소프트웨어 플랫폼에 구현하여 실험한 결과, $R-{\lambda}$ 모델 율 제어 알고리즘으로 율 제어 하여 부호화 한 경우 Y-PSPNR(peak signal to perceptual noise ratio)에 대한 BD-rate 는 평균 9.4%의 이득이 있었음을 확인하였다.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.19 no.2
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• pp.89-95
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• 2008

Subjective voice evaluation is necessary and important to assess the voice disorders in addition to objective voice evaluation. Subjective voice evaluation is divided into examiner and examinee subjective voice assessment. The examiner assessment represents perceptual judgment to the patient's voice such as GRBAS scale, Buffalo voice profile, consensus auditory perceptual evaluation of voice (CAPE- V) and so on. The examinee assessment consists of indirect method including voice handicap index (VHI), voice outcome survey (VOS), voice symptom scale (VoiSS), voice related quality of life (V-ROQL) and direct method which is called patient's self-subjective voice rating. This review article describes a general rule, advantages and pitfalls about GRBAS scale, VHI and patient's self-subjective voice rating which are presently most representative voice assessment tools.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• Phonetics and Speech Sciences
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• v.6 no.3
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• pp.63-72
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• 2014

The current study assessed the utility of acoustic analyses the most commonly used in routine clinical voice assessment including perturbation, nonlinear dynamic analysis, and Spectral/Cepstrum analysis based on signal typing of dysphonic voices and investigated their applicability of clinical acoustic analysis methods. A total of 70 dysphonic voice samples were classified with signal typing using narrowband spectrogram. Traditional parameters of %jitter, %shimmer, and signal-to-noise ratio were calculated for the signals using TF32 and correlation dimension(D2) of nonlinear dynamic parameter and spectral/cepstral measures including mean CPP, CPP_sd, CPPf0, CPPf0_sd, L/H ratio, and L/H ratio_sd were also calculated with ADSV(Analysis of Dysphonia in Speech and VoiceTM). Auditory perceptual analysis was performed by two blinded speech-language pathologists with GRBAS. The results showed that nearly periodic Type 1 signals were all functional dysphonia and Type 4 signals were comprised of neurogenic and organic voice disorders. Only Type 1 voice signals were reliable for perturbation analysis in this study. Significant signal typing-related differences were found in all acoustic and auditory-perceptual measures. SNR, CPP, L/H ratio values for Type 4 were significantly lower than those of other voice signals and significant higher %jitter, %shimmer were observed in Type 4 voice signals(p<.001). Additionally, with increase of signal type, D2 values significantly increased and more complex and nonlinear patterns were represented. Nevertheless, voice signals with highly noise component associated with breathiness were not able to obtain D2. In particular, CPP, was highly sensitive with voice quality 'G', 'R', 'B' than any other acoustic measures. Thus, Spectral and cepstral analyses may be applied for more severe dysphonic voices such as Type 4 signals and CPP can be more accurate and predictive acoustic marker in measuring voice quality and severity in dysphonia.