• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.77-85
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• 2015

The finger language is the part of the sign language, which is a language system that expresses vowels and consonants with hand gestures. Korean finger language has 31 gestures and each of them needs a lot of learning models for accurate recognition. If there exist mass learning models, it spends a lot of time to search. So a real-time awareness system concentrates on how to reduce search spaces. For solving these problems, this paper suggest a hierarchy HMM structure that reduces the exploration space effectively without decreasing recognition rate. The Korean finger language is divided into 3 categories according to the direction of a wrist, and a model can be searched within these categories. Pre-classification can discern a similar finger Korean language. And it makes a search space to be managed effectively. Therefore the proposed method can be applied on the real-time recognition system. Experimental results demonstrate that the proposed method can reduce the time about three times than general HMM recognition method.

• Journal of KIISE:Software and Applications
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• v.37 no.12
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• pp.946-950
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• 2010

Many sentiment categorization systems based on machine learning methods use morphological analyzers in order to extract linguistic features from sentences. However, the morphological analyzers do not generally perform well in a customer review domain because online customer reviews include many spacing errors and spelling errors. These low performances of the underlying systems lead to performance decreases of the sentiment categorization systems. To resolve this problem, we propose a feature extraction method based on simple longest matching of Eojeol (a Korean spacing unit) and phoneme patterns. The two kinds of patterns are automatically constructed from a large amount of POS (part-of-speech) tagged corpus. Eojeol patterns consist of Eojeols including content words such as nouns and verbs. Phoneme patterns consist of leading consonant and vowel pairs of predicate words such as verbs and adjectives because spelling errors seldom occur in leading consonants and vowels. To evaluate the proposed method, we implemented a sentiment categorization system using a SVM (Support Vector Machine) as a machine learner. In the experiment with Korean customer reviews, the sentiment categorization system using the proposed method outperformed that using a morphological analyzer as a feature extractor.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.119-129
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• 2019

Traditional speech training in acting education focused on the technical aspects of expressing the lines such as finding long/short syllables in the word, exercising articulation of consonants and vowels, and practicing diction etc. There was a limit on this education to transform written words to vivid verbal words. The lines become live when the actor sees the concrete mental images hidden in the words while speaking the lines. I will bring the knowledge of cognitive brain science and NLP(Neural Linguistic Programming) to investigate what mental images are and why mental images are fundamental elements of thought and emotion. In addition to that, I will examine how the muscles of the body react in the process of visualization of delicate mental images (subordinate form) and how to use the responsive muscles to express speaking materials such as intensity, pause, pitch, intonation etc. Conclusion, I will enumerate the obstacles encountered by actors in the course of practicing mental images, and suggest 'activation of breathing' as a thesis of the follow-up paper to eliminate those obstacles. This process, I intend to make mental images to be the concrete and practical information that can be applied to speak the dialogue in the play.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.2
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• pp.157-165
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• 2015

The purpose of this study is to analyse literacy of children from multicultural backgrounds, and identify cognitive-linguistic predictors that can affect their literacy. First, the higher-grade students showed better cognitive-linguistic variables in reading and writing performance. Second, it has been noted that the predictor variable of reading in children from multicultural backgrounds was homeostasis in visual form, which is a sub-variable of visual perception. This implies that detained characteristics play an important role in reading prerequisite. Therefore it can be said that it is more important to recognise features and clues about the details than reading familiar words. Furthermore, learning consonants and vowels should come first rather than studying letters at the first stages of learning Korean.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1
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• pp.31-39
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• 1995

In this paper, we have constructed phoneme discriminant filters [PDF] according to the linear discriminant function. These discriminant filters do not follow the heuristic rules by the experts but the mathematical methods in iterative learning. Proposed system. is based on the piecewise linear classifier and error correction learning method. The segmentation of speech and the classification of phoneme are carried out simutaneously by the PDF. Because each of them operates independently, some speech intervals may have multiple outputs. Therefore, we introduce the unified coefficients by the output unification process. But sometimes the output has a region which shows no response, or insensitive. So we propose time windows and median filters to remove such problems. We have trained this system with the 549 monosyllables uttered 3 times by 3 male speakers. After we detect the endpoint of speech signal using threshold value and zero crossing rate, the vowels and consonants are separated by the PDF, and then selected phoneme passes through the following PDF. Finally this system unifies the outputs for competitive region or insensitive area using time window and median filter.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.333-342
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• 2012

This paper presents a vowel onset point (VOP) detection method based on the human auditory system. This method maps the "perceptual" frequency scale, i.e. Mel scale onto a linear acoustic frequency, and then establishes a series of Triangular Mel-weighted Filter Bank simulate the function of band pass filtering in human ear. This nonlinear critical-band filter bank helps greatly reduce the data dimensionality, and eliminate the effect of harmonic waves to make the formants more prominent in the nonlinear spaced Mel spectrum. The sum of mel spectrum peaks energy is extracted as feature for each frame, and the instinct at which the energy amplitude starts rising sharply is detected as VOP, by convolving with Gabor window. For the single-word database which contains 12 vowels articulated with different kinds of consonants, the experimental results showed a good average detection rate of 72.73%, higher than other vowel detection methods based on short-time energy and zero-crossing rate.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.10-16
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• 1999

In this paper, we propose a concatenation-based speech synthesizer using CVC(consonant-vowel-consonant) speech segments extracted from an undesigned continuous speech corpus. Natural synthetic speech can be generated by a proper modelling of coarticulation effects between phonemes and the use of natural prosodic variations. In general, CVC synthesis unit shows smaller acoustic degradation of speech quality since concatenation points are located in the consonant region and it can properly model the coarticulation of vowels that are effected by surrounding consonants. In this paper, we analyze the characteristics and the number of required synthesis units of 4 types of speech synthesis methods that use CVC synthesis units. Furthermore, we compare the speech quality of the 4 types and propose a new synthesis method based on the most promising type in terms of speech quality and implementability. Then we implement the method using the speech corpus and synthesize various examples. The CVC speech segments that are not in the speech corpus are substituted by demonstrate speech segments. Experiments demonstrate that CVC speech segments extracted from about 100 Mbytes continuous speech corpus can produce high quality synthetic speech.

• Journal of KIISE
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• v.43 no.11
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• pp.1307-1314
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• 2016

Virtual Hangul keyboards like Chun-Ji-In, Narat-Gul, and QWERTY are based on eyesight recognition, in which input letter positions are fixed in the smartphone environment. The input method of a fixed-position style is not very convenient for visually impaired individuals. In order to resolve the issue of inconvenience of the Hangul input system, we propose a new paradigm of the finger-touch based Hangul input system that does not need eyesight recognition of input buttons. For the convenience of learning the touch-motion based keyboard, finger touches are designed by considering the shape and frequencies of Hangul vowels and consonants together with the preference of fingers. The base position is decided by the first touch of the screen, and the finger-touch keyboard is used in the same way for all the other touch-style devices, regardless of the differences in size and operation system. In this input method, unique finger-touch motions are assigned for Hangul letters that significantly reduce the input errors.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.41-50
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• 2020

This paper deals with the Braille Education System which complements the shortcomings of the existing Braille Learning Products. An application dedicated to the blind is configured to perform full functions through touch gestures and voice guidance for user convenience. Braille kit is produced for educational purposes through Arduino and 3D printing. The system supports the following functions. First, the learning of the most basic braille, such as initial consonants, final consonant, vowels, abbreviations, etc. Second, the ability to check learned braille by solving step quizzes. Third, translation of braille. Through the experiment, the recognition rate of touch gestures and the accuracy of braille expression were confirmed, and in case of translation, the translation was done as intended. The system allows blind people to learn braille efficiently.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.407-412
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• 2019

In this paper, we propose a technique for processing of speech recognition in korean words. Speech recognition is a technology that converts acoustic signals from sensors such as microphones into words or sentences. Most foreign languages have less difficulty in speech recognition. On the other hand, korean consists of vowels and bottom consonants, so it is inappropriate to use the letters obtained from the voice synthesis system. That improving the conventional structure speech recognition can the correct words recognition. In order to solve this problem, a new algorithm was added to the existing speech recognition structure to increase the speech recognition rate. Perform the preprocessing process of the word and then token the results. After combining the result processed in the Levenshtein distance algorithm and the hashing algorithm, the normalized words is output through the consonant comparison algorithm. The final result word is compared with the standardized table and output if it exists, registered in the table dose not exists. The experimental environment was developed by using a smartphone application. The proposed structure shows that the recognition rate is improved by 2% in standard language and 7% in dialect.