• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.893-898
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• 1994

In this paper, the influence of voice source estimation and modeling on speech synthesis and coding is examined and then their new estimation and modeling techniques are proposed and verified by computer simulation. It is known that the existing speech synthesizer produced the speech which is dull and inanimated. These problems are arised from the fact that existing estimation and modeling techniques can not give more accurate voice parameters. Therefore, in this paper we propose a new voice source estimation algorithm and modeling techniques which can not give more accurate voice parameters. Therefore, in this paper we propose a new voice source estimation algorithm and modeling techniques which can represent a variety of source characteristics. First, we divide speech samples in one pitch region into four parts having different characteristics. Second, the vocal-tract parameters and voice source waveforms are estimated in each regions differently using sequential SVD. Third, we propose composite source model as a new voice source model which is represented by weighted sum of pre-defined basis functions. And finally, the weights and time-shift parameters of the proposed composite source model are estimeted uning EM(estimate maximize) algorithm. Experimental results indicate that the proposed estimation and modeling methods can estimate more accurate voice source waveforms and represent various source characteristics.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.703-705
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• 1999

In this paper, we introduce the direction of arrival(DOA) estimation of distributed signal based on the improved ESPRIT algorithm. Most research on the estimation of DOA has been performed based on the assumption that the signal sources are point sources. However, we consider a two-dimensional distributed signal source model using improved ESPRIT algorithm. In the distributed signal source model, a source is represented by two parameters, the azimuth angle and elevation angle. We address the estimation of the elevation and azimuth angles of distributed sources based on the parametric source modeling in the three-dimensional space with two uniform linear arrays. The array output vector is obtained by integrating a steering vector over all direction of arrival with the weighting of a distributed source density function. We also develop an efficient estimation procedures that can reduce the computational complexity. Some examples are shown to demonstrate explicity the estimation procedures under the distributed signal source model.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.206-215
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• 2014

Acoustic signal is crucial for the autonomous navigation of underwater vehicles. For this purpose, this paper presents a method of acoustic source localization. The proposed method is based on the probabilistic estimation of time delay of acoustic signals received by two hydrophones. Using Bayesian update process, the proposed method can provide reliable estimation of direction angle of the acoustic source. The acquired direction information is used to estimate the location of the acoustic source. By accumulating direction information from various vehicle locations, the acoustic source localization is achieved using extended Kalman filter. The proposed method can provide a reliable estimation of the direction and location of the acoustic source, even under for a noisy acoustic signal. Experimental results demonstrate the performance of the proposed acoustic source localization method in a real sea environment.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3E
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• pp.25-30
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• 2001

In angle of arrival estimation, the direction of a signal is usually assumed to be a point. If the direction of a signal is distributed due to some reasons in real surroundings, however, angle of arrival estimation techniques based on the point source assumption may result in poor performance. In this paper, we consider angle of arrival estimation when the signal sources are distributed. A parametric source model is proposed, and the estimation techniques based on the well-known maximum likelihood technique is considered under the model. In addition, Various statistical properties of the estimation errors were obtained.

• MALSORI
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• no.67
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• pp.121-133
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• 2008

To estimate directions of multi-sound sources, we consider an approach based on zero crossings which provided more robust results to diffuse noise than the conventional cross-correlation-based method [6][7]. In reverberant environments, the performance of source direction estimation can be improved by using signal components through direct paths from sources to microphones. Since a cepstral prefiltering technique [8] removes the effect of reverberation, we propose a source direction estimation method which can find out intervals of the direct-path components by comparing original and cepstral-prefiltered envelopes. Simulations demonstrate that the proposed method can improve the performance of source direction estimation in reverberant environments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.276-283
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• 2012

In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.80.2-80
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• 2002

The problem of sound source localization is to determine the position of sound sources using the measurement of the acoustic signals received by microphones. To develop a good sound source localization system which is applicable to a mobile platform such as robots, a time delay estimator with low computational complexity and robustness to background noise or reverberations is necessary. In this paper, an explicit adaptive time delay estimation method for a sound source localization system is proposed. Proposed explicit adaptive time estimation algorithm employs direct adaptation of the delay parameter using a transform-based optimization technique, rather than...

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3431-3437
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• 2021

In this study, one-dimensional gamma ray source positions are estimated using a plastic scintillating optical fiber, two photon counters and via data processing with a machine learning algorithm. A nonlinear regression algorithm is used to construct a machine learning model for the position estimation of radioactive sources. The position estimation results of radioactive sources using machine learning are compared with the theoretical position estimation results based on the same measured data. Various tests at the source positions are conducted to determine the improvement in the accuracy of source position estimation. In addition, an evaluation is performed to compare the change in accuracy when varying the number of training datasets. The proposed one-dimensional gamma ray source position estimation system with plastic scintillating fiber using machine learning algorithm can be used as radioactive leakage scanners at disposal sites.

• Journal of Ocean Engineering and Technology
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• v.33 no.5
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• pp.421-426
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• 2019

The directivity of an underwater sound source should be measured in an acoustically open field such as a calm sea or lake, or an anechoic water tank facility. However, technical difficulties arise when practically implementing this in open fields. Signal processing-based techniques such as a sound intensity method and near-field acoustic holography have been adopted to overcome the problem, but these are inefficient in terms of acquisition and maintenance costs. This study established a simple directivity estimation technique with data acquisition, filtering, and analysis tools. A numerical simulation based on an acoustic radiosity method showed that the technique is practicable for sound source directivity estimation in a diffused reverberant acoustic field like a reverberant water tank.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.4
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• pp.387-396
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• 2003

A field study was conducted during the summer time of 2002 to determine compositions of volatile organic compounds (VOCs) emitted from vehicles and to develop source emission profiles that is applied to CMB model to estimate the source contribution of certain area. Source emission profile is widely used for the estimation of source contribution by the chemical mass balance model and have to be developed applicable for the target area of estimation. This study was aimed to develop source emission profile and estimation of source contribution of VOCs after application of the chemical mass balance (CMB) receptor model. After considering the emission inventory and other research results for the VOCs in Seoul, Korea, the sources like vehicle emission (tunnel), gas station (gasoline, diesel), solvent usage (painting operation, dry cleaning, graphic art), and gas fuels were selected for the major VOCs sources. Furthermore, ambient air samples were simultaneously collected from 09:00 to 11:00 for four days at eight different official air quality monitoring sites as receptors in Seoul during summer of 2001. Source samples were collected by canisters, and then about seventy volatile organic compounds were analyzed by gas chromatography with flame ionization detector (GC/FID). Based on both the developed source profiles and the database of the receptors, CMB model was intensively applied to estimate mass contribution of VOCs sources. Examining the source profile from the vehicle, the portion of alkanes of VOCs was highest, and then the portion of aromatics such toluene, m/p-xylene were followed. In case of gas fuel. they have their own components; the content of butane, propane, ethane was higher than any other component according to the fuel usage. The average of the source apportionment on VOCs for 8 sites showed that the major sources were vehicle emission and gas fuels. The vehicle emission source was revealed as having the highest contribution with an average of 49.6%, and followed by solvent with 21.3%, gas fuel with 16.1%, gasoline with 13.1%.