• Journal of the Korea Computer Industry Society
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• v.2 no.2
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• pp.195-202
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• 2001

In this paper, we show a study on how to model a phoneme of which acoustic feature is changed according to both left-hand and right-hand phonemes. For this purpose, we make a comparative study on two kinds of algorithms; a unit reduction algorithm and decision tree modeling. The unit reduction algorithm uses only statistical information while the decision tree modeling uses statistical information and Korean acoustical information simultaneously. Especially, we focus on how to model context-dependent phonemes based on decision tree modeling. Finally, we show the recognition rate when context-dependent phonemes are obtained by the decision tree modeling.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.287-289
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• 2005

This paper presents a hybrid neural network system which used a Self-Organizing Map and Multilayer Perceptron for the problem of Malay syllables speech recognition. The novel idea in this system is the usage of a two-dimension Self-organizing feature map as a sequential mapping function which transform the phonetic similarities or acoustic vector sequences of the speech frame into trajectories in a square matrix where elements take on binary values. This property simplifies the classification task. An MLP is then used to classify the trajectories that each syllable in the vocabulary corresponds to. The system performance was evaluated for recognition of 15 Malay common syllables. The overall performance of the recognizer showed to be 91.8%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.109-114
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• 2011

In this paper, we apply a context awareness based on Gaussian mixture model (GMM) to a sound reinforcement for hearing impaired. In our approach, the harmful sound amplified through the sound reinforcement algorithm according to context awareness based on GMM which is constructed as Mel-frequency cepstral coefficients (MFCC) feature vector from sound data. According to the experimental results, the proposed approach is found to be effective in the various acoustic environments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.149-154
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• 2001

Ship owners are demanding quieter vessels since crews have become more sensitive to their acoustic environment. Accordingly, designers of shipyards need to respond intelligently to the challenging requirements of delivering a quiet vessel. In early design stage, to predict shipboard noise the statistical approach is preferred to other methods because of simplicity. However, since the noise characteristics of the ships vary continuously with the environments, it is necessary to update the prediction formula with data base management system. This paper describes the feature of database program with the prediction method. Database management programs with GUI, are applied to Intranet system that is accessible by any users. Statistical approach to the prediction of A-weighted noise level in ship cabins, based on multiple regression analysis, is conducted. The noise levels in ship cabins are mainly affected by the parameters of the deadweight, the type of ship, the relative location of engines and cabins, the type of deckhouse, etc. As a result of verification, the formulas ensure the accuracy of 3 ㏈ in 83 % of cabins.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.391-399
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• 2018

In this paper, we construct and compare various guitar chord classification systems using perceptron neural network and convolutional neural network without pre-processing other than Fourier transform to identify the optimal chord classification system. Conventional guitar chord classification schemes use, for better feature extraction, computationally demanding pre-processing techniques such as stochastic analysis employing a hidden markov model or an acoustic data filtering and hence are burdensome for real-time chord classifications. For this reason, we construct various perceptron neural networks and convolutional neural networks that use only Fourier tranform for data pre-processing and compare them with dataset obtained by playing an electric guitar. According to our comparison, convolutional neural networks provide optimal performance considering both chord classification acurracy and fast processing time. In particular, convolutional neural networks exhibit robust performance even when only small fraction of low frequency components of the data are used.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.441-445
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• 2009

We have developed a real-time software tool to extract a speech feature vector whose time sequences consist of three groups of vector components; the phonetic/acoustic features such as formant frequencies, the phonemic features as outputs on neural networks, and some distances of Japanese phonemes. In those features, since the phoneme distances for Japanese five vowels are applicable to express vowel articulation, we have designed a switch, a volume control and a color representation which are operated by pronouncing vowel sounds. As examples of those vowel interface, we have developed some speech training tools to display a image character or a rolling color ball and to control a cursor's movement for aurally- or vocally-handicapped children. In this paper, we introduce the functions and the principle of those systems.

• Speech Sciences
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• v.9 no.4
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• pp.201-214
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• 2002

In the Japanese language, there is a phonological contrast between not only initial stops, but also non initial in voiced and voiceless sounds. But in the Korean language, voiced sounds do not appear in the initial. Due to this, pronunciation of voiced sounds in the initial will be difficult for Korean. Through this research, I analyzed the minimal pairs by voiced/voiceless sounds of Japanese and Korean, and perception experiment in which Japanese listened to Korean speakers' pronunciations. Japanese pronunciations showed distinct acoustic differences between voiced and voiceless stops, especially in VOT. The duration of vowels after voiced stops was longer than that of voiceless ones. Vowel pitches after voiceless stops were higher. On the other hands, Korean showed three patterns of voiced sounds. There were-VOT values as native speakers, +VOT, and nasal formant tended to occur before prenasalized stops. Koreans pronounced voiceless sounds in strong aspirated, unaspirated, or tense sounds. Finally, Japanese judged sounds with not only -VOT values and prenasalized, but also with +VOT values as voiced. This suggests that we may not consider VOT values as the unique feature of voicing, and that such other phonetic characteristics as the following vowel lengthening should be included here.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.7 no.1
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• pp.32-38
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• 1996

The preservation of the voice-producing mechanism is an important feature in the management of laryngeal cancer by radiotherapy. But, radiation therapy has certain side effects such as mucositis, tissue edema, necrosis and fibrosis which could effect on normal voice production. Several subjective studies that used questionnaires and auditory perceptual judgements of voice have been interpreted to mean that radiation results in a normal or near-normal voice. Objective evidence of the status of vocal function after radiation treatment, however, is still lacking. We analyzed the changes that occur in voice parameters in a group of patients undergoing radiation therapy, in order to determine the effect of radiation on voice quality. In this study acoustic, aerodynamic measures of vocal function were used to determine the characteristics of voice production. We found that voice parameters in early glottic cancer changed meaningfully comparing to normal larynx with or without radiation and radiation therapy has an little effect on normal larynx.

• Phonetics and Speech Sciences
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• v.6 no.2
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• pp.9-20
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• 2014

In this paper, we propose an automatic fluency evaluation algorithm for English speaking tests. In the proposed algorithm, acoustic features are extracted from an input spoken utterance and then fluency score is computed by using support vector regression (SVR). We estimate the parameters of feature modeling and SVR using the speech signals and the corresponding scores by human raters. From the correlation analysis results, it is shown that speech rate, articulation rate, and mean length of runs are best for fluency evaluation. Experimental results show that the correlation between the human score and the SVR score is 0.87 for 3 speaking tests, which suggests the possibility of the proposed algorithm as a secondary fluency evaluation tool.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.72.1-72.1
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• 2016

Current and planned large-volume surveys such as the Sloan Digital Sky Survey extended Baryon Oscillation Spectroscopic Survey (SDSS IV-eBOSS) or the Dark Energy Spectroscopic Instrument (DESI) will use Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) to map the cosmic web up to z~1.7, and will allow one to accurately constrain cosmological models and obtain crucial information on the nature of dark energy and the expansion history of the Universe in novel epochs - particularly by measuring the Baryon Acoustic Oscillation (BAO) feature with improved accuracy. To this end, we present here a study of the spatial distribution and clustering of a sample of LRGs and ELGs obtained from a sub-volume of the MultiDark simulation complemented by different semi-analytic prescriptions, and investigate how these two different populations trace the cosmic web at different redshift intervals - along with their synergy. This is the first step towards the interpretation of upcoming ELG and LRG data.