• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.2
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• pp.93-100
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• 1986

We analyzed Korean CV mono-syllables consisted of concatenation of consonants/k, t, p, g/, their fortis and rough sound and vowels/a, e, o, u, I/by the PARCOR technique, and then we synthesized those speech by means of the phoneme synthesis controlling the analyzed data. In the speech analysis, the duration of consonants decreases in the rough sound, the lenis and the fortis in turns. And also the gain of them decreases in the same tendency. The pitch period increases more and more in vowels following the rough sound, the fortis and the lenis in turns. We synthesized the lenis and the fortis by controlling the duration and the gain of the rough sound, and vowels following the fortis and the rough sound by controlling the pitch period and the duration of vowels following the lenis. As the results, the synthesized speech quality is good and we make certain it is possible to make a rule to the phonome synthesis in Korea speech.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.179-186
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• 2005

We can extract spectrum of the voices and analyze those, after employing features of frequency that voices have. In the spectrum of the voices monophthongs are thought to be stable, but when a consonant(s) meet a vowel(s) in a syllable or a word, there is a lot of changes. This becomes the biggest obstacle to phoneme speech recognition. In this study, using Mel Cepstrum and Mel Band that count Frequency Band and auditory information, we analyze the spectrums that each and every consonant and vowel has and the changes in the voices reftects auditory features and make it a system. Finally we are going to present the basis that can segment the voices by an unit of phoneme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.7
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• pp.618-627
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• 1990

In this paper a new algorithm for separation of contacting subpattern and connective feature extraction of strokes is proposed. This algorithm is able to classification of the type of contacting parts, connective feature extreaction of strokes, separate the phoneme of contacting parts between strokes, classify the character types by feature classification of connecting parts and analysis of connecting attribute. Also, shape normalize into formal patterns and decide on the input pattern from position value of bending feature of this normalized shape and make an recognition experiment by neural network using BEP learining algorithm. This algorithm represents the good achievement ratio by separation of phoneme, classification of character type, connective feature extraction of stroke and recognition experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.1026-1035
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• 1997

In this paper, we studied for phoneme recognition using GPFN and PNN as a kind of RBFN. The structure of RBFN is similar to a feedforward networks but different from choosing of activation function, reference vector and learnign algorithm in a hidden layer. Expecially sigmoid function in PNN is replaced by one category included exponential function. And total calculation performance is high, because PNN performs pattern classification with out learning. In phonemerecognition experiment with 5 vowel and 12 consant, recognition rates of GPFN and PNN as a kind of RBFN reflected statistic characteristic of speech are higher than ones of MLP in case of using test data and quantizied data by VQ and LVQ.

• Phonetics and Speech Sciences
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• v.3 no.4
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• pp.95-102
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• 2011

The purpose of this study was to identify the characteristics of the phonological discrimination ability and phonological working memory of 10 typically developing children aged 4, and 10 other children with Specific Language Impairments whose language age is similar. In orders to compare their phonological discrimination ability among phonological awareness, discrimination tasks were conducted at the syllable and phoneme levels. Also, in order to compare their phonological working memory, the subjects repeated nonsense syllables. The research results may be summarized as follows: First, the children with Specific Language Impairments demonstrated a lower performance than the typically developing children in phonological discrimination ability at both syllable and phoneme levels, and the difference between the groups was statistically significant. Second, the children with Specific Language Impairments exhibited a lower phonological working memory performance in all syllables compared with normal children. Although there was no significant difference in 2 and 3 syllables, a significant difference appeared as the length of the syllables became longer from 4 to 6 syllables. It is deemed necessary to conduct research into qualitative and quantitative differences through an formal assessment of the phonological awareness and phonological working memory of children with Specific Language Impairments.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.198-206
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• 1996

Using eighteen text materials from various goners of present-day Japanese, we collected phonologically reduced forms frequently observed in conversational Japanese, and classified them in search of unified explanation of phonological reduction phenomena. We found 7,516 cases of reduced forms which we divided into 43 categories according to the types of phonological changes they have undergone. The general tendencies ale that deletion and fusion of a phoneme or an entire syllable takes place frequently, resulting in the decrease in the number of syllable. Typical examples frequently observed throughout the materials are : $~/noda/{\rightarrow}~/nda/,{\;}-/teiru/{\rightarrow}~/teru/,{\;}~/dewa/{\rightarrow}~/zja/,{\;}~/tesimau/{\rightarrow}~/cjau/$. From morphosyntactic point of view phonological reduction often occurs at the NP and VP morpheme boundaries. The following findings are drawn from phonological observations of reduction. (1) Vowels are more easily deleted than consonants. (2) Bilabials(/m/, /b/, and /w/ are the most likely candidates for deletion. (3) In a concatenation of vowels, closed vowels are absorbed into open vowels, or two adjacent vowels come to create another vowel, in which case reconstruction of the original sequence is not always predictable. (4) Alveolars are palatalized under the influence of front vowels. (5) Regressive assimilation takes place in a syllable starting with ill, changing the entire syllable into phonological choked sound or a syllabic nasal, depending on the voicing of following phoneme.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.108-115
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• 1996

This paper proposes an algorithm and a model topology for the connected speech recognition using Discrete Hidden Markov Models. A proposed model uses diphone and triphone model which consider the recognition rate and recognisable vocabulary. Considering more exact inter- phoneme segmentation and execution speed of algorithm, 4 states have to exist in diphone model where the first state and the last state are keeping a steady state, the other states hold a transient state. 7 states have to exist in triphone model where 7 states are specified and improved to 3 steady states and 4 transition states. Also, the proposed speech recognition algorithm is designed to detect the inter-phoneme segmentation during the recognition processing.

• Speech Sciences
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• v.8 no.4
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• pp.229-241
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• 2001

Using eighteen texts from various genera of present-day Japanese, I collected phonologically reduced forms frequently observed in conversational Japanese, and classified them in search of a unified. explanation of phonological phenomena. I found 7,516 cases of reduced forms which I divided into 43 categories according to the types of phonological changes they have undergone. The general tendencies are that deletion and fusion of a phoneme or an entire syllable takes place frequently, resulting in the decrease in the number of syllables. From a morphosyntactic point of view, phonological reduction often occurs at the NP and VP morpheme boundaries. The following findings are drawn from phonetical observations of reduction. (1) Vowels are more easily deleted than consonants. (2) Bilabials ([m], [b], and [w]) are the most likely candidates for deletion. (3) In a concatenation of vowels, closed vowels are absorbed into open vowels, or two adjacent vowels come to create another vowel, in which case reconstruction of the original sequence is not always predictable. (4) Alveolars are palatalized under the influence of front vowels. (5) Regressive assimilation takes place in a syllable starting with [r], changing the entire syllable into a phonological choked sound or a syllabic nasal, depending on the voicing of the following phoneme.

• Phonetics and Speech Sciences
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• v.1 no.1
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• pp.63-67
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• 2009

In this paper, in order to protect music copyrights, we propose a music identification system which is scalable to the number of pieces of registered music and robust to signal-level variations of registered music. For its implementation, we define the new concepts of 'music word' and 'music phoneme' as recognition units to construct 'music acoustic models'. Then, with these concepts, we apply the HMM-based framework used in continuous speech recognition to identify the music. Each music file is transformed to a sequence of 39-dimensional vectors. This sequence of vectors is represented as ordered states with Gaussian mixtures. These ordered states are trained using Baum-Welch re-estimation method. Music files with a suspicious copyright are also transformed to a sequence of vectors. Then, the most probable music file is identified using Viterbi algorithm through the music identification network. We implemented a music identification system for 1,000 MP3 music files and tested this system with variations in terms of MP3 bit rate and music speed rate. Our proposed music identification system demonstrates robust performance to signal variations. In addition, scalability of this system is independent of the number of registered music files, since our system is based on HMM method.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.125-132
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• 2010

In vocabulary recognition has unseen tri-phone appeared when recognition training. This system has not been created beginning estimation figure of model parameter. It's bad points could not be created that model for phoneme data. Therefore it's could not be secured accuracy of Gaussian model. To improve suggested Gaussian model to optimized method of model parameter using probability distribution. To improved of confidence that Gaussian model to optimized of probability distribution to offer by accuracy and to support searching of phoneme data. This paper suggested system performance comparison as a result of recognition improve represent 1.7% by out-of vocabulary rejection algorithm using normalization confidence.