• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.49-60
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• 1995

This paper is a study on the design and implementation of the Korean Text-to-Speech system which is used for a small and simple system. In this paper, a parameter synthesis method is chosen for speech syntheiss method, we use PARCOR(PARtial autoCORrelation) coefficient which is one of the LPC analysis. And we use phoneme for synthesis unit which is the basic unit for speech synthesis. We use PARCOR, pitch, amplitude as synthesis parameter of voice, we use residual signal, PARCOR coefficients as synthesis parameter of unvoice. In this paper, we could obtain the 60% intelligibility by using the residual signal as excitation signal of unvoiced sound. The result of synthesis experiment, synthesis of a word unit is available. The controlling of phoneme duration is necessary for synthesizing of a sentence unit. For setting up the synthesis system, PC 486, a 70[Hz]-4.5[KHz] band pass filter for speech input/output, amplifier, and TMS320C30 DSP board was used.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.57-63
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• 2012

In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using $16^{th}$ order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.20-29
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• 2013

The compression of video data is intended for real-time transmission of band-limited channels. Compressed video bit-streams are very sensitive to transmission error. If we lose packets or receive them with errors during transmission, not only the current frame will be corrupted, but also the error will propagate to succeeding frames due to the spatio-temporal predictive coding structure of sequences. Error detection and concealment is a good approach to reduce the bad influence on the reconstructed visual quality. To increase concealment efficiency, we need to get some more accurate error detection algorithm. In this paper, We hide specific data into the motion vector difference of each macro-block, which is obtained from the procedure of inter prediction mode in H.264/AVC. Then, the location of errors can be detected easily by checking transmitted specific data in decoder. We verified that the proposed algorithm generates good performances in PSNR and subjective visual quality through the computer simulation by H.324M mobile simulation tool.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.304-309
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• 2002

We propose the computation reduction method of real root method that is mainly used in the CELP (Code Excited Linear Prediction) vocoder. The real root method is that if polynomial equations have the real roots, we are able to find those and transform them into LSP. However, this method takes much time to compute, because the root searching is processed sequentially in frequency region. In this paper, to reduce the computation time of real root, we compare the real root method with two methods. In first method, we use the mal scale of searching frequency region that is linear below 1 kHz and logarithmic above. In second method, The searching frequency region and searching interval are ordered by each coefficient's distribution. In order to compare real root method with proposed methods, we measured the following two. First, we compared the position of transformed LSP (Line Spectrum Pairs) parameters in the proposed methods with these of real root method. Second, we measured how long computation time is reduced. The experimental results of both methods that the searching time was reduced by about 47% in average without the change of LSP parameters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1370-1376
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• 2012

This paper proposes a gender recognition algorithm which classifies a male or female speaker. In this paper, characteristic vectors for the male and female speaker are analyzed, and recognition experiments for the proposed gender recognition by a neural network are performed using these characteristic vectors for the male and female. Input characteristic vectors of the proposed neural network are 10 LPC (Linear Predictive Coding) cepstrum coefficients, 12 LPC cepstrum coefficients, 12 FFT (Fast Fourier Transform) cepstrum coefficients and 1 RMS (Root Mean Square), and 12 LPC cepstrum coefficients and 8 FFT spectrum. The proposed neural network trained by 20-20-2 network are especially used in this experiment, using 12 LPC cepstrum coefficients and 8 FFT spectrum. From the experiment results, the average recognition rates obtained by the gender recognition algorithm is 99.8% for the male speaker and 96.5% for the female speaker.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.10 no.2
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• pp.119-123
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• 1999

Background and Objectives : Conditions such as muscle atrophy, stretching of strap muscles, and continued craniofacial growth factors have been cited as contributing to the changes observed in the vocal tract structure and function in elderly speakers. The purpose of the present study is to compare F$_1$ and F$_2$ frequency levels in elderly and young adult male and female speakers producing a series of vowels ranging from high-front to low-back placement. Material and Methods : The subjects were two groups of young adults(10 males, 10 females, mean age 21 years old range 19-24 years) and two groups of elderly speakers(10 males, 10 females, mean age 67 years : range 60-84 years). Each subject participated in speech pathologist to be a speaker of unimpared standard Korean. The headphone was positioned 2 cm from the speakers lips. Each speaker sustained the five vowels for 5 s. Formant frequency measures were obtained from an analysis of linear predictive coding in CSL model 4300B(Kay co). Results : Repeated measure AVOVA procedures were completed on the $F_1$ and $F_2$ data for the male and female speakers. $F_2$ formant frequency levels were proven to be significantly lower fir elderly speakers. Conclusions : We presume $F_2$ vocal cavity(from the point of tongue constriction to lip) lengthening in elderly speakers. The research designed to observe dynamic speech production more directly will be needed.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.957-963
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• 2007

In this paper, Nonlinear Autoregressive (NAR) method based on Least Square-Support Vector Regression (LS-SVR) is introduced and tested for nonlinear sustained vowel modeling. In the database of total 43 sustained vowel of Benign Vocal Fold Lesions having aperiodic waveform, this nonlinear synthesizer near perfectly reproduced chaotic sustained vowels, and also conserved the naturalness of sound such as jitter, compared to Linear Predictive Coding does not keep these naturalness. However, the results of some phonation are quite different from the original sounds. These results are assumed that single-band model can not afford to control and decompose the high frequency components. Therefore multi-band model with wavelet filterbank is adopted for substituting single band model. As a results, multi-band model results in improved stability. Finally, nonlinear sustained vowel modeling using NAR based on LS-SVR can successfully reconstruct synthesized sounds nearly similar to original voiced sounds.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.2
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• pp.43-48
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• 2017

The underwater transients signals contain the characteristics of complexity, time varying, nonlinear, and short duration. So it is very hard to model for these signals with reference patterns. In this paper we separate the whole length of signals into some short duration of constant length with overlapping frame by frame. The 20th LPC(Linear Predictive Coding) coefficients are extracted from the original signals using Durbin algorithm and applied to neural network. The 65% of whole signals were learned and 35% of the signals were tested in the neural network with two hidden layers. The types of the whales for sound classification are Blue whale, Dulsae whale, Gray whale, Humpback whale, Minke whale, and Northern Right whale. Finally, we could obtain more than 83% of classification rate from the test signals.

• Animal Bioscience
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• v.37 no.8
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• pp.1367-1376
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• 2024

Objective: Parathyroid hormone like hormone (PTHLH), as an essential factor for bone growth, is involved in a variety of physiological processes. The aim of this study was to explore the role of PTHLH gene in the growth of antlers. Methods: The coding sequence (CDS) of PTHLH gene cDNA was obtained by cloning in sika deer (Cervus nippon), and the bioinformatics was analyzed. The quantitative real-time polymerase chain reaction (qRT-PCR) was used to analyze the differences expression of PTHLH mRNA in different tissues of the antler tip at different growth periods (early period, EP; middle period, MP; late period, LP). Results: The CDS of PTHLH gene was 534 bp in length and encoded 177 amino acids. Predictive analysis results revealed that the PTHLH protein was a hydrophilic protein without transmembrane structure, with its secondary structure consisting mainly of random coil. The PTHLH protein of sika deer had the identity of 98.31%, 96.82%, 96.05%, and 94.92% with Cervus canadensis, Bos mutus, Oryx dammah and Budorcas taxicolor, which were highly conserved among the artiodactyls. The qRT-PCR results showed that PTHLH mRNA had a unique spatio-temporal expression pattern in antlers. In the dermis, precartilage, and cartilage tissues, the expression of PTHLH mRNA was extremely significantly higher in MP than in EP, LP (p<0.01). In the mesenchyme tissue, the expression of PTHLH mRNA in MP was significantly higher than that of EP (p<0.05), but extremely significantly lower than that of LP (p<0.01). The expression of PTHLH mRNA in antler tip tissues at all growth periods had approximately the same trend, that is, from distal to basal, it was first downregulated from the dermis to the mesenchyme and then continuously up-regulated to the cartilage tissue. Conclusion: PTHLH gene may promote the rapid growth of antler mainly through its extensive regulatory effect on the antler tip tissue.

• Journal of Korean Academy of Nursing
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• v.29 no.5
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• pp.1087-1102
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• 1999

Diabetes mellitus, a universal and prevalent chronic disease, is projected to be one of the most formidable worldwide health problems in the 21st century. For those living with diabetes, there is a need for self-care skills to manage a complex medical regimen. Self-efficacy which refers to one's belief in his/her capability to monitor and perform the daily activities required to manage diabetes has be found to be related to self-care. The concept of self-efficacy comes from social cognitive theory which maintains that cognitive mechanism mediate the performance of behavior. The literature cites several research studies which show a strong relationship between self-efficacy and self-care behavior. Meta-analysis is a technique that enables systematic review and quantitative integration of the results from multiple primary studies that are relevant to a particular research question. Therefore, this study was done using meta-analysis to quantitatively integrate the results of independent research studies to obtain numerical estimates of the overall effect of a self-efficacy with diabetic patient on self-care behaviors. The research proceeded in three stages : 1) literature search and retrieval of studies in which self-efficacy was related to self-care, 2) coding, and 3) calculation of mean effect size and data analysis. Seventeen studies which met the research criteria included study population of adults with diabetes, measures of self-care and measures of self-efficacy as a predictive variable. Computation of effect size was done on DSTAT which is a statistical computer program specifically designed for meta-analysis. To determine the effect of self-efficacy on self-care practice homogeneity tests were conducted. Pooled effect size estimates, to determine the best subvariable for composite variables, metabolic control variables and component of self-efficacy and self-care, indicated that the effect of self-efficacy composite on self-care composite was moderate to large. The weighted mean effect size of self-efficacy composite and self-care composite were ＋.76 and the confidence interval was from ＋.66 to ＋.86 with the number of subjects being 1,545. The total for this meta-analysis result showed that the weighted mean effect sizes ranged from ＋.70 to ＋1.81 which indicates a large effect. But since reliabilities of the instruments in the primary studies were low or not stated, caution must be applied in unconditionally accepting the results from these effect sizes. Meta-analysis is a useful took for clarifying the status of knowledge development and guiding decision making about future research and this study confirmed that there is a relationship between self-efficacy and self-care in patients with diabetes. It, thus, provides support for nurses to promote self-efficacy in their patients. While most of the studies included in this meta-analysis used social cognitive theory as a framework for the study, some studies use Fishbein & Ajzen's attitude model as a model for active self-care. Future research is needed to more fully define the concept of self-care and to determine what it is that makes patients feel competent in their self-care activities. The results of this study showed that self-efficacy can promote self-care. Future research is needed with experimental design to determine nursing interventions that will increase self-efficacy.