• Proceedings of the IEEK Conference
• /
• 2002.06d
• /
• pp.397-400
• /
• 2002

This paper has been studied speech enhancement method in noisy environment. By mean of that we prefer human auditory mechanism which is perfect system and applied wavelet transform. Multi-resolution of wavelet transform make possible multiband spectrum analysis like human ears. This method was verified very effective way in noisy speech enhancement.

• Journal of Broadcast Engineering
• /
• v.20 no.1
• /
• pp.164-170
• /
• 2015

This paper deals with the adaptation of classification model in the binary mask approach to suppress noise in the noisy environment. The binary mask estimation approach is known to improve speech intelligibility of noisy speech. However, the same type of noisy data for the test data should be included in the training data for building the classification model of binary mask estimation. The eigenvoice adaptation is applied to the noise-independent classification model and the adapted model is used as noise-dependent model. The results are reported in Hit rates and False alarm rates. The experimental results confirmed that the accuracy of classification is improved as the number of adaptation sentences increases.

• KIEAE Journal
• /
• v.3 no.2
• /
• pp.33-36
• /
• 2003

The influence of the visual information on the sound perception would be considerable. Furthermore, if the sound perception ranges in noisiness or annoyance beyond the loudness, it will depend much more on the shape of the visual information. This paper aims to estimate the influence of the several kinds of visual information on the perception of road traffic noise by means of the psycho-acoustic test method. The findings of present study on the influence of visual information on subjective noise perception are summarized as follows: Presenting visual images of mild and comfortable scenery reduced the noise perception reaction at the less noisy environments not exceeding 65 dB(A). At highly noisy environments exceeding 65 dB(A), however, the noise perception can be reduced by strong image of waterfall. Even eliminating the road traffic image may be helpful. Visual image of waterfall reduced the noise perception at all levels. It is inferred that the road traffic noise perception can be effectively ameliorated by presenting strong and real landscape images at any noisy environment.

• The Journal of the Acoustical Society of Korea
• /
• v.27 no.7
• /
• pp.386-393
• /
• 2008

This paper proposes a new approach for speech enhancement in highly nonstationary noisy environments. The spectral subtraction (SS) is a well known technique for speech enhancement in stationary noisy environments. However, in real world, noise is mostly nonstationary. The proposed method uses an auto control parameter for an adaptive threshold to work well in highly nonstationary noisy environments. Especially, the auto control parameter is affected by a linear function associated with an a posteriori signal to noise ratio (SNR) according to the increase or the decrease of the noise level. The proposed algorithm is combined with spectral subtraction (SS) using a hangover scheme (HO) for speech enhancement. The performances of the proposed method are evaluated ITU-T P.835 signal distortion (SIG) and the segment signal to-noise ratio (SNR) in various and highly nonstationary noisy environments and is superior to that of conventional spectral subtraction (SS) using a hangover (HO) and SS using a minimum statistics (MS) methods.

• Phonetics and Speech Sciences
• /
• v.6 no.3
• /
• pp.165-169
• /
• 2014

Intelligibility of speech transmitted to listeners can significantly be degraded in noisy environments such as in auditorium and in train station due to ambient noises. Noise-masked speech signal is hard to be recognized by listeners. Among the conventional methods to improve speech intelligibility, consonant-vowel intensity ratio (CVR) approach reinforces the powers of overall consonants. However, excessively reinforced consonant is not helpful in recognition. Furthermore, only some of consonants are improved by the CVR approach. In this paper, we propose the corrective weighting (CW) approach that reinforces the powers of consonants according to syllable-type such as consonant-vowel-consonant (CVC), consonant-vowel (CV) and vowel-consonant (VC) in Korean differently, considering the level of listeners' recognition. The proposed CW approach was evaluated by the subjective test, Comparison Category Rating (CCR) test of ITU-T P.800, showed better performance, that is, 0.18 and 0.24 higher than the unprocessed CVR approach, respectively.

• Journal of Multimedia Information System
• /
• v.3 no.2
• /
• pp.21-26
• /
• 2016

Our networked world has been growing exponentially fast. The explosion in volume of machine-to-machine (M2M) transactions threatens to exceed the transport capacity of the networks that link them. Therefore, it is quite essential to reconsider the tradeoff between using many data sets versus using good data sets. We focus on this tradeoff in the context of the quality of information aggregated from many sensors in a noisy environment. We start with a basic theoretical model considered in the famous "CEO problem'' in the field of information theory. From a point of view of large deviations, we successfully find a simple statement for the optimal strategies under the limited network capacity condition. Moreover, we propose an open problem for a sensor network scenario and report a numerical result.

• Phonetics and Speech Sciences
• /
• v.9 no.2
• /
• pp.103-110
• /
• 2017

The pole filtering concept has been successfully applied to cepstral feature normalization techniques for noise-robust speech recognition. In this paper, it is proposed to apply the pole filtering selectively only to the speech intervals, in order to further improve the recognition performance for short utterances in noisy environments. Experimental results on AURORA 2 task with clean-condition training show that the proposed selectively pole-filtered cepstral mean normalization (SPFCMN) and selectively pole-filtered cepstral mean and variance normalization (SPFCMVN) yield error rate reduction of 38.6% and 45.8%, respectively, compared to the baseline system.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.3166-3168
• /
• 2000

This paper proposed variable threshold dual rate ADPCM coding method which is modified from the standard ADPCM of ITU G.726 for speech quality improvement. The speech quality of variable threshold dual rate ADPCM is better than single rate ADPCM at noisy environment without increasing the complexity by using ZCR(Zero Crossing Rate). In this case, ZCR is used to divide input signal samples into two categories(noisy & speech). The samples with higher ZCR is categorized as the noisy region and the samples with lower ZCR is categorized as the speech region. Noisy region uses higher threshold value to be compressed by 16Kbps for reduced bit rates and the speech region uses lower threshold value to be compressed by 40Kbps for improved speech quality. Comparing with the conventional ADPCM, which adapts the fixed coding rate. the proposed variable threshold dual rate ADPCM coding method improves noise character without increasing the bit rate. For real time applications, ZCR calculation was considered as a simple method to obtain the background noise information for preprocess of speech analysis such as FFT and the experiment showed that the simple calculation of ZCR can be used without complexity increase. Dual rate ADPCM can decrease the amount of transferred data efficiently without increasing complexity nor reducing speech quality. Therefore result of this paper can be applied for real-time speech application such as the internet phone or VoIP.

• Journal of Preventive Medicine and Public Health
• /
• v.28 no.4 s.51
• /
• pp.773-782
• /
• 1995

The purpose of this study is to reveal how the road traffic noise influences on the response of teachers and students, which composed of conversation, studying, relaxation, and physical disturbances. The research method used in this study was self-administrated questionnaire. Samples of the survey were composed of 420 persons(114 teachers and 306 students) who are exposed to traffic noise less than 65 dB(A) from two junior high schools and 410 persons(140 teachers and 270 students) from two noisy junior high schools which the road traffic noise above 65 dB(A). In the response of both of the teachers and students in noisy(above 65 dB) schools complaints of disturbances of conversation, studying, relaxation, and physical disturbances are much higher than that of less noisy schools' teachers and students(p<0.01). On the occasion of time and season, the subjects answered the traffic noise cause high troublesome and stresses in the afternoon(12:00 - 17:00) and summer respectively. It is necessary to provide governmental comprehensive and fundamental measures to improve the noisy school environments.

• Journal of the Korea Society for Simulation
• /
• v.28 no.4
• /
• pp.21-32
• /
• 2019

Inspired by the social behavior models of a bird flock or fish school, particle swarm optimization (PSO) is a popular metaheuristic optimization algorithm and has been widely used from solving a complex optimization problem to learning a artificial neural network. However, PSO is difficult to apply to many real-life optimization problems involving stochastic noise, since it is originated in a deterministic environment. To resolve this problem, this paper incorporates a resampling method called the uncertainty evaluation (UE) method into PSO. The UE method allows the particles to converge on the accurate optimal solution quickly in a noisy environment by selecting the particles' global best position correctly, one of the significant factors in the performance of PSO. The results of comparative experiments on several benchmark problems demonstrated the improved performance of the propose algorithm compared to the existing studies. In addition, the results of the case study emphasize the necessity of this work. The proposed algorithm is expected to be effectively applied to optimize complex systems through digital twins in the fourth industrial revolution.