• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.522-525
• /
• 2009

This paper proposed the content-based method of classifying filthy Phornographic video, which causes a big problem of modern society as the reverse function of internet. Audio data was used to extract the features from Phornographic video. There are frequency spectrum, autocorrelation, and MFCC as the feature of audio used in this paper. The sound that could be filthy contents was extracted, and the Phornographic was classified by measuring how much percentage of relevant sound was corresponding with the whole audio of video. For the experiment on the proposed method, The efficiency of classifying Phornographic was measured on each feature, and the measured result and comparison with using multi features were performed. I can obtain the better result than when only one feature of audio was extracted, and used.

• ETRI Journal
• /
• v.32 no.5
• /
• pp.801-809
• /
• 2010

This paper presents a statistical model-based noise suppression approach for voice recognition in a car environment. In order to alleviate the spectral whitening and signal distortion problem in the traditional decision-directed Wiener filter, we combine a decision-directed method with an original spectrum reconstruction method and develop a new two-stage noise reduction filter estimation scheme. When a tradeoff between the performance and computational efficiency under resource-constrained automotive devices is considered, ETSI standard advance distributed speech recognition font-end (ETSI-AFE) can be an effective solution, and ETSI-AFE is also based on the decision-directed Wiener filter. Thus, a series of voice recognition and computational complexity tests are conducted by comparing the proposed approach with ETSI-AFE. The experimental results show that the proposed approach is superior to the conventional method in terms of speech recognition accuracy, while the computational cost and frame latency are significantly reduced.

• Ocean Systems Engineering
• /
• v.2 no.2
• /
• pp.147-158
• /
• 2012

A time-domain simulation of a land-based Oscillating Water Column (OWC) with various irregular waves as a form of PM spectrum is performed by using a two-dimensional fully nonlinear numerical wave tank (NWT) based on the potential theory, mixed Eulerian-Lagrangian (MEL) approach, and boundary element method. The nonlinear free-surface condition inside the OWC chamber was specially devised to describe both the pneumatic effect of the time-varying pressure and the viscous energy loss due to water column motions. The quadratic models for pneumatic pressure and viscous loss are applied to the air and free surface inside the chamber, and their numerical results are compared with those with equivalent linear ones. Various wave spectra are applied to the OWC system to predict the efficiency of wave-energy take-off for various wave conditions. The cases of regular and irregular waves are also compared.

• Proceedings of the IEEK Conference
• /
• 2001.09a
• /
• pp.801-804
• /
• 2001

LSP 파라미터는 음성코덱(codec)이나 인식기에서 음성 신호를 분석하여 전송형이나 저장형 파라미터로 변환되어, 주로 저전송률 음성부호화기에 사용된다. 그러나 LPC 계수를 LSP로 변환하는 방법이 복잡하여 계산시간이 많이 소요된다는 단점이 있다[1]. 기존의 LSP 변환 방법 중 음성 부호화기에서 주로 사용하는 real root 방법은 근을 구하기 위해 주파수 영역을 순차적으로 검색하기 때문에 계산시간이 많이 소요되는 단점을 갖는다. 본 논문에서 비교 평가한 알고리즘은 첫 번째, 기존의 real root 알고리즘, 두 번째는, LSP 파라미터의 분포 특성을 조사하여 이를 토대로 검객구간의 순서와 검색간격을 달리한 경우, 세 번째는 검색 시 mel scale을 사용한 알고리즘이다. 실험결과, 기존의 real root 방식에 비하여 두 가지 방식 모두가 변환시간의 40% 이상이 감소되는데 반하여 통일한 관을 찾음을 알 수가 있었고, 특히 분포특성을 이용하여 검색순서와 간격조절을 한 경우에 있어서, 기존의 방식보다 40%이상이 감소되었다.

• Journal of Korea Multimedia Society
• /
• v.20 no.10
• /
• pp.1637-1645
• /
• 2017

Target/Nontarget classification can be divided into the study of shape estimation of the target analysing reflected echo signal and of type classification of the target using acoustical features. In active sonar system, the feature vectors are extracted from the signal reflected from the target, and an classification algorithm is applied to determine whether the received signal is a target or not. However, received sonar signals can be distorted in the underwater environments, and the spatio-temporal characteristics of active sonar signals change according to the aspect of the target. In addition, it is very difficult to collect real sea-trial data for research. In this paper, target/non-target classification were performed using real sea-trial data. Feature vectors are extracted using MFCC(Mel-Frequency Cepstral Coefficients), filterbank energy in the Fourier spectrum and wavelet domain. For the performance verification, classification experiments were performed using backpropagation neural network classifiers.

• Proceedings of the KAIS Fall Conference
• /
• 2010.05a
• /
• pp.257-260
• /
• 2010

In this paper, we propose the computation reduction methods of LSP(Line spectrum pairs) transformation that is mainly used in CELP vocoders. In order to decrease the computational time in real root method the characteristic of four proposed algorithms is as the following. First, scheme to reduce the LSP transformation time uses mel scale. Developed the second scheme is the control of searching order by the distribution characteristic of LSP parameters. Third, scheme to reduce the LSP transformation time uses voice characteristics. Developed the fourth scheme is the control of searching interval and order by the distribution characteristic of LSP parameters. As a result of searching time, computational amount, transformed LSP parameters, SNR, MOS test, waveform of synthesized speech, spectrogram analysis, searching time is reduced about 37.5%, 46.21%, 46.3%, 51.29% in average, computational amount is reduced about 44.76%, 49.44%, 47.03%, 57.40%. But the transformed LSP parameters of the proposed methods were the same as those of real root method.

• Phonetics and Speech Sciences
• /
• v.12 no.3
• /
• pp.55-63
• /
• 2020

Voice conversion can be applied to various voice processing applications. It can also play an important role in data augmentation for speech recognition. The conventional method uses the architecture of voice conversion with speech synthesis, with Mel filter bank as the main parameter. Mel filter bank is well-suited for quick computation of neural networks but cannot be converted into a high-quality waveform without the aid of a vocoder. Further, it is not effective in terms of obtaining data for speech recognition. In this paper, we focus on performing voice-to-voice conversion using only the raw spectrum. We propose a deep learning model based on the transformer network, which quickly learns the voice conversion properties using an attention mechanism between source and target spectral components. The experiments were performed on TIDIGITS data, a series of numbers spoken by an English speaker. The conversion voices were evaluated for naturalness and similarity using mean opinion score (MOS) obtained from 30 participants. Our final results yielded 3.52±0.22 for naturalness and 3.89±0.19 for similarity.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.3
• /
• pp.304-309
• /
• 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 Academia-Industrial cooperation Society
• /
• v.8 no.3
• /
• pp.563-568
• /
• 2007

We propose the computation reduction method of real root method that is used in the EVRC(Enhanced Variable Rate Codec) system. 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. But, the important characteristic of LSP is that most of coefficients are occurred in specific frequency region. So, to reduce the computation time of real root, we used the met scale that is linear below 1kHz and logarithmic above. In order to compare real root method with proposed method, we measured the following two. First, we compared the position of transformed LSP(Line Spectrum Pairs) parameters in the proposed method with these of real root method. Second, we measured how long computation time is reduced. The experimental result is that the searching time was reduced by about 48% in average without the change of LSP parameters.

• Development and Reproduction
• /
• v.5 no.2
• /
• pp.181-187
• /
• 2001

Seasonal changes and circadian rhythm of plasma prolactin(PRL) concentration in mammals are mediated by melatonin. Pinealectomy or denervation of the pineal gland produces an increase in plasma PRL level. In the rat placenta several members of the PRL family gene are expressed during the late pregnancy. However, the full spectrum of their expression mechanisms and regulatory factors are not elucidated yet. Present study aimed to investigate the local expression of the melatonin receptor la(Me $l_{la}$ ) gene and the effect of melatonin on expression of prolactin-like protein A(PLP-A), a member of the PRL-family gene in the rat placenta. According to the RT-PCR, northern blot and in situ hybridization experiments, Me $l_{la}$ gene was locally expressed in the rat placenta, Me $l_{la}$ mRNA was localized mainly in the placental junctional and labyrinth zones. Interestingly, junctional zone of the placenta showed strong expression of Me $l_{la}$ at daytime(16:00) than at nighttime(22:00). Melatonin agonist, chlorornelatonin decreased the PLP-A mRNA levels in the rat placenta. These results suggest that melatonin coupled with Me $l_{la}$ , may act as a regulation factor that mediates the expression of the PLP-A gene in the rat placenta.