• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.529-536
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• 2016

In this paper we proposed an unsupervised algorithm to estimate the reverberation time (RT) directly from the reverberant speech signal. For estimation process we use maximum likelihood estimation (MLE) which is a very well-known and state of the art method for estimation in the field of signal processing. All existing RT estimation methods are based on the decay rate distribution. The decay rate can be obtained either from the energy envelop decay curve analysis of noise source when it is switch off or from decay curve of impulse response of an enclosure. The analysis of a pre-existing method of reverberation time estimation is the foundation of the proposed method. In one of the state of the art method, the reverberation decay is modeled as a Laplacian distribution. In this paper, the proposed method models the reverberation decay as a Gamma distribution along with the unification of an effective technique for spotting free decay in reverberant speech. Maximum likelihood estimation technique is then used to estimate the RT from the free decays. The method was motivated by our observation that the RT of a reverberant signal when falls in specific range, then the decay rate of the signal follows Gamma distribution. Experiments are carried out on different reverberant speech signal to measure the accuracy of the suggested method. The experimental results reveal that the proposed method performs better and the accuracy is high in comparison to the state of the art method.

• 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 the Society of Naval Architects of Korea
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• v.61 no.1
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• pp.1-7
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• 2024

Underwater sound speed is an important analysis parameter on an estimation of the underwater radiated noise (URN) emitted from vessels. This paper aims to present an underwater sound speed measurement procedure using a cross-correlation of time-domain acoustic signals and validate the procedure through an experiment in a reverberant water tank. For the purpose, time-domain acoustic signals transmitted by a Gaussian pulse excitation from an acoustic projector have been measured at 20 hydrophone positions in the reverberant water tank. Then, the sound speed in water has been calculated by a linear regression using 190 cross-correlation cases of distances and time lags between the received signals and the result has been compared with those estimated by the existing empirical formulae. From the result, it is regarded that the presented experimental procedure to measure an underwater sound speed is reliably applicable if the time resolution is sufficiently high in the measurement.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1845-1851
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• 2007

Background noise and room reverberation are two causes of degradation in speech in listening situations. Many algorithms developed to enhance reverberant speech. In this paper we propose a dereverberation method for enhancement of speech using modified the linear prediction(LP) residual in reverberant room condition. The proposed dereberberation method based on the fact that the signification excitation of the vocal tract system takes place at the instant of glottal closure in voiced speech. Our method used delay information form each sensor, and we need reverberant signals from 3 sensors. We obtain a new LP residual signal using modified IP residual combination which derived form weighting of the LP residual and the Hilbert transform of LP residual. The nature of the coherently added Hilbert envelop has several large amplitude spikes because of the effects of noise and reverberation. This residual of the clean speech is used to excite the time-varying all-pole filter to obtain the enhanced speech. We achieved simulation of proposed algorithm for performance analysis in reverberation environment. The proposed algorithm improves substantially the quality of reverberant speech.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.89-95
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• 2006

The performance of blind source separation(BSS) using independent component analysis (ICA) declines significantly in a reverberant environment. A post-processing method proposed in this paper was designed to remove the residual component precisely. The proposed method used modified NLMS(normalized least mean square) filter in frequency domain, to estimate cross-talk path that causes residual cross-talk components. Residual cross-talk components in one channel is correspond to direct components in another channel. Therefore, we can estimate cross-talk path using another channel input signals from adaptive filter. Step size is normalized by input signal power in conventional NLMS filter, but it is normalized by sum of input signal power and error signal power in modified NLMS filter. By using this method, we can prevent misadjustment of filter weights. The estimated residual cross-talk components are subtracted by non-stationary spectral subtraction. The computer simulation results using speech signals show that the proposed method improves the noise reduction ratio(NRR) by approximately 3dB on conventional FDICA.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.503-514
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• 2021

Reverberation in speech signals tends to significantly degrade the performance of the Blind Source Separation (BSS) system. Especially in online systems, the performance degradation becomes severe. Methods based on joint diagonalizability constraints have been recently developed to tackle the problem. To improve the quality of separated speech, in this paper, we add the proposed de-reverberation method to the online BSS algorithm based on the constraints in reverberant environments. Through experiments on the WSJCAM0 corpus, the proposed method was compared with the existing online BSS algorithm. The performance evaluation by the Signal-to-Distortion Ratio and the Perceptual Evaluation of Speech Quality demonstrated that SDR improved from 1.23 dB to 3.76 dB and PESQ improved from 1.15 to 2.12 on average.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.6
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• pp.655-662
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• 2012

Gas leakage in an oil refinery causes damage to the environment and unsafe conditions. Therefore, it is necessary to develop a technique that is able to detect the location of the leakage and to filter abnormal gas-leakage signals from normal background noise. In this study, the adaptation filter of the finite impulse response (FIR) least mean squares (LMS) algorithm and a cross-correlation function were used to develop a leakage-predicting program based on LABVIEW. Nitrogen gas at a high pressure of 120 kg/$cm^2$ and the assembled equipment were used to perform experiments in a reverberant chamber. Analysis of the data from the experiments performed with various hole sizes, pressures, distances, and frequencies indicated that the background noise occurred primarily at less than 1 kHz and that the leakage signal appeared in a high-frequency region of around 16 kHz. Measurement of the noise sources in an actual oil refinery revealed that the noise frequencies of pumps and compressors, which are two typical background noise sources in a petrochemical plant, were 2 kHz and 4.5 kHz, respectively. The fact that these two signals were separated clearly made it possible to distinguish leakage signals from background noises and, in addition, to detect the location of the leakage.