• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.4
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• pp.269-275
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• 2003

In this paper, We examined auditory threshold and critical ratio of amberjack seriola dumerili, in the Jeju Island coastal waters, to find out hearing ability of the fish. The auditory threshold level, critical ratio and hearing index of amberjack were determinded by conditioning method using a sound coupled with electric shock in the condition of ambient noise or white noise in an experimental water tank. The audio-signals of pure tone and electric shock were from 80 HZ to 800 Hz and DC 7 V, respectively. Values for the critical ratios were calculated in terms of the masked thresholds using the noise projected to stable spectrum levels at all measurement frequencies of background noise. Masking noises were in the spectrum level range of 65 dB∼75 dB $(re 1{\mu}Pa\sqrt{Hz})$. The auditory thresholds of amberjack within the test the frequencies were most sensitive at 300HZ as 94.5 dB. The critical ratios of fishes ranged from 36.4 to 52.8 dB. The noise spectrum level that started masking was about 58∼72 dB within frequencies.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.103-112
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• 1999

In this paper, a speaker-independent isolated world recognition system for a car navigation system is implemented using a general digital signal processor. This paper presents a method combining SNR normalization with RAS as a noise processing method. The semi-continuous hidden markov model is adopted and TMS320C31 is used in implementing the real-time system. Recognition word set is composed of 69 command words for a car navigation system. Experimental results showed that the recognition performance has a maximum of 93.62% in case of a combination of SNR normalization and spectral subtraction, and the performance improvement rate of the system is 3.69%, Presented noise processing method showed good speech recognition performance in 5dB SNR in car environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.273-278
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• 2004

In this paper, the recurrent neural networks (RNN) is applied to compensate for HMM recognition algorithm, which is commonly used as main recognizer. Among these recurrent neural networks, the multi-layer recurrent neural prediction model (MRNPM), which allows operating in real-time, is used to implement learning and recognition, and HMM and MRNPM are used to design a hybrid-type main recognizer. After testing the designed speech recognition algorithm with Korean number pronunciations (13 words), which are hardly distinct, for its speech-independent recognition ratio, about 5% improvement was obtained comparing with existing HMM recognizers. Based on this result, only optimal (recognition) codes were extracted in the actual DSP (TMS320C6711) environment, and the embedded speech recognition system was implemented. Similarly, the implementation result of the embedded system showed more improved recognition system implementation than existing solid HMM recognition systems.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.21-29
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• 2019

Take-over requests in semi-autonomous cars must be handled properly in the case of road obstacles or curved roads in order to avoid accidents. In these situations, situation awareness and appropriate decision making are essential for distracted drivers. This study used a driving simulator to investigate the components of auditory-visual information systems that affect safety, workload, and trust. Auditory information consisted of either voice guidance providing situation awareness for the take-over or a beep sound that only alerted the driver. Visual information consisted of either a screen showing how to maneuver the vehicle or only an icon indicating a take-over situation. By providing auditory information that increased situation awareness and visual information that aided decision making, trust and safety increased, while workload decreased. These results suggest that the levels of situation awareness and decision making ability affect trust, safety, and workload for drivers.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.60-65
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• 2018

In this paper, a covariance matrix and modulogram are proposed for realizing amphibian sound classification using CNN (Convolutional Neural Network). First of all, a database is established by collecting amphibians sounds including endangered species in natural environment. In order to apply the database to CNN, it is necessary to standardize acoustic signals with different lengths. To standardize the acoustic signals, covariance matrix that gives distribution information and modulogram that contains the information about change over time are extracted and used as input to CNN. The experiment is conducted by varying the number of a convolutional layer and a fully-connected layer. For performance assessment, several conventional methods are considered representing various feature extraction and classification approaches. From the results, it is confirmed that convolutional layer has a greater impact on performance than the fully-connected layer. Also, the performance based on CNN shows attaining the highest recognition rate with 99.07 % among the considered methods.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.85-89
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• 1996

In this paper, transition constrained Hidden Markov Model(HMM) in which the transition between states occur only within prescribed time slot is proposed and the performance is evaluated in the noisy environment. The transition constrained HMM can explicitly limit the state durations and accurately de scribe the temporal structure of speech signal simply and efficiently. The transition constrained HMM is not only superior to the conventional HMM but also require much less computation time. In order to evaluate the performance of the transition constrained HMM, speaker independent isolated word recognition experiments were conducted using semi-continuous HMM with the noisy speech for 20, 10, 0 dB SNR. Experiment results show that the proposed method is robust to the environmental noise. The 81.08% and 75.36% word recognition rates for conventional HMM was increased by 7.31% and 10.35%, respectively, by using transition constrained HMM when two kinds of noises are added with 10dB SNR.

• The Journal of the Acoustical Society of Korea
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• v.16 no.6
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• pp.25-35
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• 1997

Most of speech analysis methods developed up to date are based on second order statistics, and one of the biggest drawback of these methods is that they show dramatical performance degradation in noisy environments. On the contrary, the methods using higher order statistics(HOS), which has the property of suppressing Gaussian noise, enable robust feature extraction in noisy environments. In this paper we propose a text-independent speaker identification system using higher order statistics and compare its performance with that using the conventional second-order-statistics-based method in both white and colored noise environments. The proposed speaker identification system is based on the vector quantization approach, and employs HOS-based voiced/unvoiced detector in order to extract feature parameters for voiced speech only, which has non-Gaussian distribution and is known to contain most of speaker-specific characteristics. Experimental results using 50 speaker's database show that higher-order-statistics-based method gives a better identificaiton performance than the conventional second-order-statistics-based method in noisy environments.

• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.38-43
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• 1996

This paper compares the recognition performances of feature vectors known to be robust to the environmental noise. And, the speech subtraction technique is combined with the noise robust feature to get more performance enhancement. The experiments using SMC(Short time Modified Coherence) analysis, root cepstral analysis, LDA(Linear Discriminant Analysis), PLP(Perceptual Linear Prediction), RASTA(RelAtive SpecTrAl) processing are carried out. An isolated word recognition system is composed using semi-continuous HMM. Noisy environment experiments usign two types of noises:exhibition hall, computer room are carried out at 0, 10, 20dB SNRs. The experimental result shows that SMC and root based mel cepstrum(root_mel cepstrum) show 9.86% and 12.68% recognition enhancement at 10dB in compare to the LPCC(Linear Prediction Cepstral Coefficient). And when combined with spectral subtraction, mel cepstrum and root_mel cepstrum show 16.7% and 8.4% enhanced recognition rate of 94.91% and 94.28% at 10dB.

• The Journal of the Acoustical Society of Korea
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• v.15 no.4
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• pp.83-92
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• 1996

This paper describes Lombard effect compensation and noise suppression so as to reduce speech recognition error in noisy environments. Lombard effect is represented by the variation of spectral envelope of energy normalized word and the variation of overall vocal intensity. The variation of spectral envelope can be compensated by linear transformation in cepstral domain. The variation of vocal intensity is canceled by spectral magnitude normalization. Spectral subtraction is use to suppress noise contamination, and band-pass filtering is used to emphasize dynamic features. To understand Lombard effect and verify the effectiveness of the proposed method, speech data are collected in simulated noisy environments. Recognition experiments were conducted with contamination by noise from automobile cabins, an exhibition hall, telephone booths in down town, crowded streets, and computer rooms. From the experiments, the effectiveness of the proposed method has been confirmed.

• Journal of Korean Medical classics
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• v.19 no.2 s.33
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• pp.310-315
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• 2006

아건강상태(亞健康狀態)에 처하여 있는 환자는 양의학적으로 뚜렷한 병리적 변화를 찾아보기가 쉽지 않다. 그러나 중의학의 병기이론을 근거로 하면 아건강상태(亞健康狀態)는 일정한 병리적 상태에 처한 것으로 인식된다. 즉 인체의 음양과 기혈이 편파(偏頗)되어 있으며 단지 그 변화가 초기단계에 있기 때문에 병태(病態)적 요인에 비하여 정도(程度)적인 차이가 있는 것으로 인식된다. 중의학이 건강에 대한 인식은 ‘천인상응(天人相應)’과 ‘음평양비(陰平陽秘)’, ‘정신내치(精神乃治)’란 관념이다. 주로 사람과 자연환경 및 외부사회간의 상호관계, 그리고 체내의 음양조화를 이룬 동태평형(動態平衝)을 중요시한다. 즉 인체의 기혈평형과 장부기능의 협조(協調)를 강조하고 기기(氣機)의 조창(調暢)이 건강의 근본(根本)이라고 인식한다. 시대적인 관계로 중의학에는 아건강상태(亞健康狀態)란 용어가 없지만 2000여년 전(前)에 성서(成書)된 중의학의 경전거작(經典巨作)인 ${\ulcorner}$내경(內經)${\lrcorner}$ 속에 일찍이 ‘미병(未病)’이란 개념(槪念)과 치미병(治未病)의 관념을 제출하였다. 이는 중의학이 미병선방(未病先防)의 의학사상을 나타내었고 주로 치병지미성(治病之未成), ‘치기미전(治其未傳)’, ‘차후방복’등 세 가지 방면의 내용을 제시된다. 또한 중의학은 양생학(養生學)에 대하여 특별히 중시하였고,${\ulcorner}$내경(內經)${\lrcorner}$에 대량(大量)의 편폭(篇福)으로 어떻게 양생하고 정기(正氣)를 보호해야 한다는 방법이 소개 되어 있다. 후세(後世) 역대의가(歷代醫家)는 그 내용을 더욱 충실(充實)케 하고 발전시켰다. 근대(近代)에 이르러서 중의학술(中醫學術)에 특유한 내용인 '미병학(未病學)'이 형성되었고, 그 이론체계 속에 아건강상태(亞健康狀態)의 예방과 치료에 관한 내용이 포함되어 있다.