• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.775-780
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• 2013

This paper proposes a speaker-dependent speech recognition algorithm which can classify the gender for male and female speakers in white noise and car noise, using a neural network. The proposed speech recognition algorithm is trained by the neural network to recognize the gender for male and female speakers, using LPC (Linear Predictive Coding) cepstrum coefficients. In the experiment results, the maximal improvement of total speech recognition rate is 96% for white noise and 88% for car noise, respectively, after trained a total of six neural networks. Finally, the proposed speech recognition algorithm is compared with the results of a conventional speech recognition algorithm in the background noisy environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1571-1576
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• 2013

This paper proposes an improvement algorithm of signal-to-noise ratios (SNRs) for speech signals under noisy environments. The proposed algorithm first estimates the SNRs in a low SNR, mid SNR and high SNR areas, in order to improve the SNRs in the speech signal from background noise, such as white noise and car noise. Thereafter, this algorithm subtracts the noise signal from the noisy speech signal at each bands using a spectrum sharpening method. In the experiment, good signal-to-noise ratios (SNR) are obtained for white noise and car noise compared with a conventional spectral subtraction method. From the experiment results, the maximal improvement in the output SNR results was approximately 4.2 dB and 3.7 dB better for white noise and car noise compared with the results of the spectral subtraction method, in the background noisy environment, respectively.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.575-577
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• 2009

Traditionally, tire made a role of function, which is supporting vehicle load, making brake, transferring, traction etc. So, there are a lot of studying for the tire. especially, tire noise is one of the most important parameter in the car noise. this thesis shows the method how to reduce the tire noise by using the optimal pitch sequence. Because the optimal pitch sequence prevents tire from generating the pure tone while driving the car on the ground.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.302-307
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• 2010

Development of light-weight high speed train (HST) based on distributed motor control with the top speed of 350 km/hr has engendered a need for abatement of the interior noise of the train cabin. The development of noise abatement measures is crucial at the design stage of the train car since the noise transmission characteristics of the car structure directly influences the cabin interior noise. Since the transmission loss measurement using the entire car structure is often not feasible, especially at the initial stages of the train development, investigation of transmission characteristics using small-scale reverberation chamber can furnish useful alternative source of predicting the noise level. In the present study, white noise is generated at source and transmission loss estimated by performing measurement of a specimen in a scaled reverberation chamber. Comparison of measured values with the previously derived numerical values show good agreement in the overall trend but appreciable quantitative differences still remain.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.04a
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• pp.203-208
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• 1996

This paper consider the control for the vehicle suspension system using electro-rheological damper. The study is performed by using of FLC(Fuzzy Logic Controller). The model used in the simulation is quarter car and the road disturbance is regarded as white noise random process with zero mean. Proposed control technique shows good agreement compared with the result from the conventional on-off/bang-bang type control technique.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1793-1801
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• 2016

Speech enhancement is a challenging problem due to the diversity of noise sources and their effects in different applications. The goal of speech enhancement is to improve the quality and intelligibility of speech by reducing noise. Many research works in speech enhancement have been accomplished in English and other European Languages. There has been limited or no such works or efforts in the past in the context of Tamil speech enhancement in the literature. The aim of the proposed method is to reduce the background noise present in the Tamil speech signal by using wavelets. New modified thresholding function is introduced. The proposed method is evaluated on several speakers and under various noise conditions including White Gaussian noise, Babble noise and Car noise. The Signal to Noise Ratio (SNR), Mean Square Error (MSE) and Mean Opinion Score (MOS) results show that the proposed thresholding function improves the speech enhancement compared to the conventional hard and soft thresholding methods.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.87-101
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• 2002

In this paper, we proposes the car plate recognition and describe the parking control system using the proposed car plate recognition algorithm. The car plate recognition system using color information and fuzzy c-means algorithm consists of the extraction part of a car plate from a car image and the recognition part of characters in the extracted car plate. This paper eliminates green noise from car image using the mode smoothing and extract plate region using green and white information of RGB color. The codes of extracted plate region is extracted by histogram based approach method and is recognized by fuzzy c-means algorithm. For experimental, we tested 80 car images. We shows that the proposed extraction method is better than that from the color information of RGB and HSI, respectively. So, we can know that the proposed car plate recognition method using fuzzy c-means algorithm was very efficient. We develop the parking control system using the proposed car plate recognition method, which showed performance improvement by the experimental results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.817-822
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• 2011

This paper first proposes the speech recognition algorithm by detection of the speech and noise sections at each frame using a neural network training by back-propagation algorithm, then proposes the spectral subtraction method which removes the noises at each frame according to detection of the speech and noise sections. In this experiment, the performance of the proposed recognition system was evaluated based on the recognition rate using various speeches that are degraded by white noise and car noise. Moreover, experimental results of the noise reduction by the spectral subtraction method demonstrate using the speech and noise sections detecting by the speech recognition algorithm at each frame. Based on measuring signal-to-noise ratio, experiments confirm that the proposed algorithm is effective for the speech by corrupted the noise using signal-to-noise ratio.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.9-17
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• 2012

One of the problems on the application of the speech recognition system in the real world is the degradation of the performance by acoustical distortions. The most important source of acoustical distortion is the additive noise. This paper describes a spectral compensation technique based on a spectral peak enhancement scheme followed by an efficient noise subtraction scheme for noise robust speech recognition. The proposed methods emphasize the formant structure and compensate the spectral tilt of the speech spectrum while maintaining broad-bandwidth spectral components. The recognition experiments was conducted using noisy speech corrupted by white Gaussian noise, car noise, babble noise or subway noise. The new technique reduced the average error rate slightly under high SNR(Signal to Noise Ratio) environment, and significantly reduced the average error rate by 1/2 under low SNR(10 dB) environment when compared with the case of without spectral compensations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.293-298
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• 1993

In ground vehicles, the increasing demand for safety and ride comfort which are trade-off relation, especially at high speeds, has led to the development od actively controlled suspensions. The LQG/LTR controller can be used to design a robust feedback control system that deals with disturbance rejection properties as well as insensitivity to modelling errors and sensor noise. And when the disturbance can not be measured but is limited within a certain frequency range, a bandpass feedback to eliminate the disturbance response can be used. In this paper, hybrid controller cosisted of bandpass feedback controller and LQG/LTR controller is applied to a quarter-car model moving on a randomly profiled road. The random road profile considered as colored noise is shaped from white noise by use of shaping filter. The performance of the hybrid control system is compared with that of an LQG/LTR controlled system.