• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.127-134
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• 2018

In this paper, we have developed the Auto Lip-Sync Maya plug-in for extracting Korean phonemes from voice data and text information based on Korean and produce high quality 3D lip-sync animation using divided phonemes. In the developed system, phoneme separation was classified into 8 vowels and 13 consonants used in Korean, referring to 49 phonemes provided by Microsoft Speech API engine SAPI. In addition, the pronunciation of vowels and consonants has variety Mouth Shapes, but the same Viseme can be applied to some identical ones. Based on this, we have developed Auto Lip-sync Maya Plug-in based on Python to enable lip-sync animation to be implemented automatically at once.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.85-93
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• 2011

Previous existing vocabulary recognition programs calculate general vector values from a database, so they can not process phonemes that form during a search. And because they can not create a model for phoneme data, the accuracy of the Gaussian model can not secure. Therefore, in this paper, we recommend use of the Bhattacharyya distance measurement method based on the features of the phoneme-thus allowing us to improve the recognition rate by picking up accurate phonemes and minimizing recognition of similar and erroneous phonemes. We test the Gaussian model optimization through share continuous probability distribution, and we confirm the heighten recognition rate. The Bhattacharyya distance measurement method suggest in this paper reflect an average 1.9% improvement in performance compare to previous methods, and it has average 2.9% improvement based on reliability in recognition rate.

• English Language & Literature Teaching
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• v.11 no.4
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• pp.97-120
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• 2005

Production and perception of second language sounds are typically influenced by second language learners' native language sounds. In this study we investigate how the Korean language influences Korean speakers' production of English alphabets. In the experiment conducted to prepare for this study 16 native speakers of Korean pronounced English alphabets. Then three native speakers of English evaluated the Korean subjects' pronunciation of them. The results show that the Korean subjects' native language (i.e., Korean) influences their production of the English alphabets. When Korean has sounds corresponding to English alphabets, the English subjects rate the Korean subjects' production of them good. For instance, Korean has voiceless stop phonemes, hence their production of English alphabets was rated good by the English subjects. The Korean subjects' production of English alphabets containing the sounds that do not exist in Korean was rated poor by the English subjects. For instance, Korean does not have voiced fricative phonemes, hence their production of English alphabets was rated poor.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.395-398
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• 1994

In this paper the word recognition using sub-model based Hidden Markov Model was studied. Phoneme models were composed of 61 phonemes in therms of Korean language pronunciation characteristic. Using this, word model was maded by serial concatenation. But, in case of this phoneme concatenation, the second and the third phoneme of syllable are overlapped in distribution at the same time. So considering this, the method that combines the second and the third phoneme to one model was proposed. And to prevent the increase in number of model, similar phonemes were combined to one, and finially, 57 models were created. In experiment proper model structure of sub-model was searched for, and recognition results were compared. So similar recognition results were maded, and overall recognition rates were increased in case of using parameter tying method.

• Speech Sciences
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• v.12 no.3
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• pp.185-200
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• 2005

The objective of this study is to examine acoustic cues in spoken French for the assessment of pronunciation which is necessary to realization of the multimedia system. The corpus is composed of simple expressions which consist of the French phonological system include all phonemes. This experiment was made on 4 male and female French native speakers and on 20 Korean speakers, university students who had learned the French language more than two years. We analyzed the recorded data by using spectrograph and measured comparative features by the numerical values. First of all, we found the mean and the deviation of all phonemes, and then chose features which had high error frequency and great differences between French and Korean pronunciations. The selected data were simplified and compared among them. After we judged whether the problems of pronunciation in each Korean speaker were either the utterance mistake or the interference of mother tongue, in terms of articulatory and auditory aspects, we tried to find acoustic features as simplified as possible. From this experiment, we could extract acoustic cues for the construction of the French pronunciation training system.

• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.17-27
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• 2009

Despite many studies on the production and perception of L2 phonemes, studies on how such phonemes are encoded lexically remain scarce. The aim of this study is to examine whether L2 learners have a perceptual problem with L2 suprasegmentals which are not present in their L1, or if they are able to perceive but not able to encode them in their lexicon. Specifically, Korean learners were tested to see if they could discriminate the vowel length differences in Japanese at the psychoacoustic level through a simple AX discrimination task. Then, a speeded lexical decision task with high phonetic variability was conducted to see whether they could use such contrasts lexically. The results showed that Korean learners of Japanese have no difficulties in discriminating Japanese vowel length contrast, but they are unable to encode such contrast in their phonological representation, even with long L2 exposure.

• The Journal of the Acoustical Society of Korea
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• v.8 no.5
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• pp.86-94
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• 1989

In this paper the method using a sign pattern( +,- ) of Mel-cepstrum coefficients as a new speech representation is proposed. Relatively stable patterns can be obtained for speech signals which has strong stationarity like vowels and nasals, and the phonemic difference according to the individuality of speakers can be absorbed without affecting characteristics of the phoneme. In this paper we show that the reduction of recognition procedure of phonemes and training procedure of phoneme models can be achieved through the representation of Korean phonemes using such a sign pattern.

• The Journal of the Acoustical Society of Korea
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• v.8 no.5
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• pp.70-77
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• 1989

In this paper, Korean language recognition using the phoneme is studied. The experiment is carried out by dividing 545 isolated words into phonemes. Using linear prediction coefficients the recognition rate of consonants, vowels, and end-consonants are $87.3(\%), 91.0(\%), 91.7(\%)$, respectively. Recognition rate of isolated words combined with the phonemes is $71.4(\%)$. Itakura-saito distortion measure is used to phoneme segmentation and phoneme recognition.

• The Journal of the Acoustical Society of Korea
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• v.8 no.1
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• pp.81-87
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• 1989

This paper discribes the method associated with modeling of Korean phonemes. Hidden Markov models(HMM's) may be viewed as an effective technique for modeling the inherent nonstationarity of speech signal. We propose a 3-state phoneme model to represent the sequentially changing characteristics of phonemes, i.e., transition-to-stationary-to-transition. Also we clarify that the duration of a phoneme is an important factor to have an effect in recognition accuracy and show that improvement in recognition rate can be obtained by using duration-dependent 3-state hidden Markov models.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.171-179
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• 1995

In many continuous speech recognition systems, phoneme is used as a basic recognition unit However, the coarticulation generated among neighboring phonemes makes difficult to recognize phonemes consistently. This paper proposes allophone as an alternative recognition unit. We have classified each phoneme into three different allophone groups by the location of phoneme within a syllable. For a recognition algorithm, time-delay neural network(TDNN) has been designed. To recognize all Korean allophones, TDNNs are constructed in modular fashion according to acoustic-phonetic features (e.g. voiced/unvoiced, the location of phoneme within a word). Each TDNN is trained independently, and then they are integrated hierarchically into a whole speech recognition system. In this study, we have experimented Korean plosives with phoneme-based recognition system and allophone-based recognition system. Experimental results show that allophone-based recognition is much less affected by the coarticulation.