• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.17 no.4 s.121
• /
• pp.363-369
• /
• 2007

The purpose of the study is to obtain acoustical information to prevent eavesdropping of the glass window. Speech intelligibility was investigated on the vibration sound detected from the glass window of a conference room. Objective test using speech transmission index(STI) was performed to estimate quantitatively the speech intelligibility. STI was determined based on tile modulation transfer function(MTF) of the room-glass window system. Using Maximum Length Sequency(MLS) signal as a sound source, impulse responses of the glass window and MTF were determined by signals from accelerometers and laser doppler vibrometer. Finally, speech intelligibility of the interior sound and window vibration were compared under different sound pressure levels and amplifier gains to confirm the effect of measurement condition on the speech intelligibility.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2022.07a
• /
• pp.553-556
• /
• 2022

본 논문에서는 거품 입자를 활용하여 시뮬레이션 장면에 맞는 소리를 효율적으로 합성할 수 있는 기법을 제안한다. 물리 기반 시뮬레이션 환경에서 소리를 표현하는 대표적인 방법은 생성과 합성이다. 사운드 생성의 경우 시뮬레이션 장면마다 물리 기반 접근법을 사용하여 소리를 생성할 수 있는데 계산 시간과 재질 표현의 어려움으로 다양한 시뮬레이션 장면에 대한 소리를 만들어 내기에는 쉽지 않다. 사운드 합성의 경우 소리 데이터를 미리 구축해야 하는 사전 준비가 필요하지만, 한 번 구축하면 비슷한 장면에서는 같은 소리 데이터를 활용할 수 있는 점이 있다. 따라서 본 논문에서는 거품 시뮬레이션의 소리 합성을 위해 소리 데이터를 구축하고 거품 입자의 효율적인 군집화를 통해 계산 시간을 줄이면서 소리의 사실감은 개선할 수 있는 사운드 합성 기법을 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2022.07a
• /
• pp.587-590
• /
• 2022

본 논문에서는 물리기반 옷감 시뮬레이션에 적합한 소리를 효율적으로 생성하기 위한 데이터 기반 합성 기법을 제안한다. 시뮬레이션에서 소리를 표현하는 방법은 크게 생성과 합성이 있지만, 합성은 실시간 애플리케이션에서 활용이 가능하기 때문에 인터랙티브한 환경에서 자주 활용되고 있다. 하지만, 데이터에 의존하기 때문에 원하는 장면에 부합하는 사운드를 합성하기는 어려우며, 기존 방법은 한 방향으로만 사운드 데이터를 검색하기 때문에 불연속으로 인한 끊김 현상이 발생한다. 본 논문에서는 양방향 사운드 합성 기법을 제시하며, 이를 통해 불연속적으로 합성되는 사운드 결과를 효율적으로 개선될 수 있음을 보여준다.

• International journal of advanced smart convergence
• /
• v.6 no.2
• /
• pp.1-8
• /
• 2017

Recently, the development of the information communication industry has made many changes in the industrial acoustic industry. Especially, it has a great influence on the change of system and equipment of acoustic system. Analog equipment is changing to digital equipment, and integrated control equipment makes it easier to operate and manage the sound system. However, the integrated control system currently on the market is only controllable for some devices. In this paper, we propose a new AoIP - based system configuration method, which enables the operation status monitoring, unmanned operation and self - diagnosis of equipment. As a result of the study, it is confirmed that the proposed system can be operated, monitored, and self - diagnosed at remote sites. It is expected that an AoIP- based sound system will be the industry standard in the future.

• Proceedings of the KSR Conference
• /
• 2006.11b
• /
• pp.144-151
• /
• 2006

Sound generated from a moving vehicle often carries information on the condition of vehicle, for example, whether it has faults or not, where the fault exists. The latter is possible especially by MFAH(moving frame acoustic holography) and beamforming method. MFAH is applicable to the sound source of pure tone or narrow band noise. For the beamforming method, we have to know what kind of wave the sound source radiates, for example, plane wave or spherical wave. That is, whether the above methods are applicable depends on the characteristics of sound source. To apply these methods to the fault detection, we have to know the characteristics of wave from faults. In this research, a machine diagnosis technique based on the above holographic approaches is introduced to find the position of faults. The signal due to faults is modeled based on the fact that the faults radiate impulsive noise, and analyzed in time and frequency domain. The way how MFAH and beamforming method can be used is introduced to find the position of source.

• Journal of Korea Multimedia Society
• /
• v.16 no.11
• /
• pp.1272-1280
• /
• 2013

In this paper, we propose an audio surveillance system which can detect and localize dangerous sounds in real-time. The location information about dangerous sounds can render a PTZ camera to be directed so as to catch a snapshot image about the dangerous sound source area and send it to clients instantly. The proposed audio surveillance system firstly detects foreground sounds based on adaptive Gaussian mixture background sound model, and classifies it into one of pre-trained classes of foreground dangerous sounds. For detected dangerous sounds, a sound source localization algorithm based on Dual delay-line algorithm is applied to localize the sound sources. Finally, the proposed system renders a PTZ camera to be oriented towards the dangerous sound source region, and take a snapshot against over the sound source region. Experiment results show that the proposed system can detect foreground dangerous sounds stably and classifies the detected foreground dangerous sounds into correct classes with a precision of 79% while the sound source localization can estimate orientation of the sound source with acceptably small error.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.05a
• /
• pp.353-358
• /
• 2002

Human's vision is mostly confined to the area in the front and we, humans heavily depend on the sense of hearing to gather information in areas out of our sight. Thus, the virtual reality system consisting of the 3D sound effect gives the user a much better sense of reality than the system without the sound effect. Virtual 3D sound technology has mainly been researched with binaural system. The conventional binaural sound systems reproduce the desired sound at two arbitrary points using two channels in 3-D space. Head movement of listener might be change the nominal acoustic transfer function and deteriorate the performance of 3D sound system based on loudspeakers that needs a crosstalk canceller. In this paper, low kinds of sensitivity functions of sphere HRTF are derived to investigate the effect of head movement on HRTF in 3D sound system. Changes of HRTF caused by rotational and translational motion of head are obtained as we calculate the derivatives of HRTF with respect to angle and distance.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.11a
• /
• pp.1053-1056
• /
• 2012

Location information is considered to be of prime importance in Vehicular Ad Hoc NETworks (VANETs) because important decisions are made based on accurate and sound location information. Vehicles exchange their whereabouts in the form of scheduled beacon messages with their neighbors. These messages contain location, speed, time, and lane information etc. In this paper we aim at the location security in VANET and emphasize on the confidentiality and integrity of location information in case of Nonline-of-Sight (NLoS). For location confidentiality we propose a geolock-based mechanism whereas for location integrity we leverage cooperation among neighbors. In case of NLoS, the verifier vehicle asks its one-hop neighbors in an efficient way to verify the claimed location of the node on his behalf. On the basis of trust values and weightage assigned to neighbors, it is decided whether the verification is sound.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.10
• /
• pp.5078-5094
• /
• 2019

In recent years, the development of drone technologies has promoted the widespread commercial application of drones. However, the ability of drone to carry explosives and other destructive materials may bring serious threats to public safety. In order to reduce these threats from illegal drones, acoustic feature extraction and classification technologies are introduced for drone sound identification. In this paper, we introduce the acoustic feature vector extraction method of harmonic line association (HLA), and subband power feature extraction based on wavelet packet transform (WPT). We propose a feature vector extraction method based on combined HLA and WPT to extract more sophisticated characteristics of sound. Moreover, to identify drone sounds, support vector machine (SVM) classification with the optimized parameter by genetic algorithm (GA) is employed based on the extracted feature vector. Four drones' sounds and other kinds of sounds existing in outdoor environment are used to evaluate the performance of the proposed method. The experimental results show that with the proposed method, identification probability can achieve up to 100 % in trials, and robustness against noise is also significantly improved.

• Journal of Korea Multimedia Society
• /
• v.20 no.2
• /
• pp.134-143
• /
• 2017

Machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines. Generally, it is very difficult to diagnose a machine fault by conventional methods based on mathematical models because of the complexity of the real world systems and the obvious existence of nonlinear factors. This study develops an automatic machine fault diagnosis system that uses pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The sounds emitted by the operating machine, a drill in this case, are obtained and analyzed for the different operating conditions. The specific machine conditions considered in this research are the undamaged drill and the defected drill with wear. Principal component analysis is first used to reduce the dimensionality of the original sound data. The first principal components are then used as the inputs of a neural network based classifier to separate normal and defected drill sound data. The results show that the proposed PCA-ANN method can be used for the sounds based automated diagnosis system.