• The Journal of the Acoustical Society of Korea
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• v.22 no.4E
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• pp.161-166
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• 2003

We present an adaptive wavelet packet based speech enhancement method with robust voice activity detection (VAD) in non-stationary noise environment. The proposed method can be divided into two main procedures. The first procedure is a VAD with adaptive wavelet packet transform. And the other is a speech enhancement procedure based on the proposed VAD method. The proposed VAD method shows remarkable performance even in low SNRs and non-stationary noise environment. And subjective evaluation shows that the performance of the proposed speech enhancement method with wavelet bases is better than that with Fourier basis.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.26-30
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• 2019

This paper proposes a new voice activity detection (VAD) method which is based on SNR and non-intrusive speech intelligibility estimation. In the conventional SNR-based VAD methods, voice activity probability is obtained by estimating frame-wise SNR at each spectral component. However these methods lack performance in various noisy environments. We devise a hybrid VAD method that uses non-intrusive speech intelligibility estimation as well as SNR estimation, where the speech intelligibility score is estimated based on deep neural network. In order to train model parameters of deep neural network, we use MFCC vector and the intrusive speech intelligibility score, STOI (Short-Time Objective Intelligent Measure), as input and output, respectively. We developed speech presence measure to classify each noisy frame as voice or non-voice by calculating the weighted average of the estimated STOI value and the conventional SNR-based VAD value at each frame. Experimental results show that the proposed method has better performance than the conventional VAD method in various noisy environments, especially when the SNR is very low.

• Journal of Chest Surgery
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• v.32 no.12
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• pp.1065-1077
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• 1999

Background : Ventricular assist devices(VADs) are being used for patients in postcvardiotomy cardiogenic shock status bridge to cardiac transplant settings and in post-myocardial infarction cardiogenic shock. The VAD which was developed at the Deparment of medical engineering in Dankook University College of Medicine was a pneumatically driven device and can maintain pulsatile flow. The goal of this study is to develop animal experimental models using the VAD and to clarify the reliability and hemodynamic property adequacy of end organ perfusion durability and severity of thrombotic-hemolytic tendency of the device. Material and Method : The pneumatic VAD was applied to 8 adult female lambs, We examined some hemodynamic parameters such as arterial blood pressure pulmonary capillary wedge pressure(pcwp) pulmonary artery pressure(PAP) left atrial pressure hour urine output cardiac index VAD flow EKG to determine the reliability of the VAD and hemodynamic compatibility of the experimental animals within 24 hours of experiment. We also observed the end organ perfusion durability of the VAD and thrombotic-hemolytic property of the VAD after 24 hours of VAD insertion. Result: We could monitor all hemodynamic parameters including pcwp PAP cardiac index EKG, adn hour urine as true clinical settings. We observed that the reliability of the VAD was excellent and the hemodynamic property of the experimental animal and end organ perfusion were adequate within 24 hours of experiment. In four lambs surviving 24 hours after insertion the reliability of the VAD and end organ perfusion were excellent and no thrombotic-hemolytic tendency was noted. However after 15 days of experiment the diaphragm of the VAD was torn and it was recommende that the durability of the VAD should be extended. Conclusion : e conclude that the pneumatic VAD developed at Dankook University Biomedical Engineering has good hemodynamic property and low thromboembolic tendency and presents adequate end organ perfusion but we noted that the durability of the device should be expanded further. It will be possible to do more reliable experiment in the future according to the animal experimental method developed in this study especially with the heart failure models.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.965-970
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• 2023

Wind profiler and wind lidar produce a vertical profile of winds in high spatiotemporal resolution in the atmospheric boundary layer. The wind lidar makes the wind vector using DBS (Doppler Beam Swinging) and VAD (Velocity Azimuth Display) methods. The DBS method has the advantage of obtaining a wind profile with a fast scan time. On the other hand, there is a restriction that requires at least two beams including vertical beam, which causes a decrease in the data acquisition rate. The VAD method was improved to produce more wind vector of the wind profiler as well as the wind lidar, which generally uses 5 beams. Fourier series was estimated with the radial velocity by the DBS method and wind vector was determined by setting the azimuth interval and applying the radial velocity by the Fourier series to the VAD method. The wind vectors were retrieved at the altitude where the wind was not calculated by the DBS method, and the results of the two methods were consistent.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.373-377
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• 2017

This paper presents a voice-activity detection (VAD) method for sound sequences with various SNRs. For real-time VAD applications, it is inadequate to employ a post-processing for the removal of burst clippings from the VAD output decision. To tackle this problem, building on the bi-level hidden Markov model, for which a state layer is inserted into a typical hidden Markov model (HMM), we formulated a robust method for VAD not requiring any additional post-processing. In the method, a forward-inference-ratio test was devised to detect the speech endpoints and Mel-frequency cepstral coefficients (MFCC) were used as the features. Our experiment results show that, regarding different SNRs, the performance of the proposed approach is more outstanding than those of the conventional methods.

• Phonetics and Speech Sciences
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• v.2 no.3
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• pp.141-148
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• 2010

In this paper, voice activity detection (VAD) for dual-channel noisy speech recognition is proposed in which spatial cues are employed. In the proposed method, a probability model for speech presence/absence is constructed using spatial cues obtained from dual-channel input signal, and a speech activity interval is detected through this probability model. In particular, spatial cues are composed of interaural time differences and interaural level differences of dual-channel speech signals, and the probability model for speech presence/absence is based on a Gaussian kernel density. In order to evaluate the performance of the proposed VAD method, speech recognition is performed for speech segments that only include speech intervals detected by the proposed VAD method. The performance of the proposed method is compared with those of several methods such as an SNR-based method, a direction of arrival (DOA) based method, and a phase vector based method. It is shown from the speech recognition experiments that the proposed method outperforms conventional methods by providing relative word error rates reductions of 11.68%, 41.92%, and 10.15% compared with SNR-based, DOA-based, and phase vector based method, respectively.

• The Journal of the Acoustical Society of Korea
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• v.26 no.1
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• pp.16-24
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• 2007

Voice activity detectors (VADs) are important in wireless communication and speech signal processing. In the conventional VAD methods. an expression for the likelihood ratio test (LRT) based on statistical models is derived. Then, speech or noise is decided by comparing the value of the expression with a threshold. We propose a new method with the modified decision rule based on the Gaussian distribution and the uniformly most power (UMP) test. This method requires the distribution of the absolute value of the incoming speech signal. Then we can obtain the final decision through the relation between the Rayleigh distributions. This VAD method can detect speech without a priori signal-to-noise ratio (SNR) which is required in the conventional VAD algorithms. Additionally, in the various VAD performance tests, the proposed VAD method is shown to be more effective than the traditional scheme.

• Phonetics and Speech Sciences
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• v.5 no.1
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• pp.11-16
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• 2013

This paper proposes robust feature extraction for accurate voice activity detection (VAD). VAD is one of the principal modules for speech signal processing such as speech codec, speech enhancement, and speech recognition. Noisy environments contain nonstationary noises causing the accuracy of the VAD to drastically decline because the fluctuation of features in the noise intervals results in increased false alarm rates. In this paper, in order to improve the VAD performance, harmonic-weighted energy is proposed. This feature extraction method focuses on voiced speech intervals and weighted harmonic-to-noise ratios to determine the amount of the harmonicity to frame energy. For performance evaluation, the receiver operating characteristic curves and equal error rate are measured.

• The Journal of the Acoustical Society of Korea
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• v.27 no.7
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• pp.372-378
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• 2008

Voice activity detectors (VAD) are important in wireless communication and speech signal processing, In the conventional VAD methods, an expression for the likelihood ratio test (LRT) based on statistical models is derived in discrete Fourier transform (DFT) domain, Then, speech or noise is decided by comparing the value of the expression with a threshold, This paper presents a new statistical VAD method based on a signal subspace approach, The probabilistic principal component analysis (PPCA) is employed to obtain a signal subspace model that incorporates probabilistic model of noisy signal to the signal subspace method, The proposed approach provides a novel decision rule based on LRT in the signal subspace domain, Experimental results show that the proposed signal subspace model based VAD method outperforms those based on the widely used Gaussian distribution in DFT domain.

• Proceedings of the Optical Society of Korea Conference
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• 2008.07a
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• pp.425-426
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• 2008

The Panda-type polarization maintaining fibers were fabricated by VAD(vapor-phase axial deposition) method. We fabricate Panda style polarization maintaining fibers that have small form factor($80{\mu}m$), high H-parameter of about $1{\times}10^{-4}/m$ and low optical loss of about 3dB/km.