• 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.

• Proceedings of the KSPS conference
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• 2004.05a
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• pp.239-242
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• 2004

An automatic pronunciation correction system provides users with correction guidelines for each pronunciation error. For this purpose, we propose a speech recognition system which automatically classifies pronunciation errors when Koreans speak a foreign language. In this paper, we also propose machine scoring methods for automatic assessment of pronunciation quality by the speech recognizer. Scores obtained from an expert human listener are used as the reference to evaluate the different machine scores and to provide targets when training some of algorithms. We use a log-likelihood score and a normalized log-likelihood score as machine scoring methods. Experimental results show that the normalized log-likelihood score had higher correlation with human scores than that obtained using the log-likelihood score.

• MALSORI
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• no.49
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• pp.1-30
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• 2004

Although Standard Korean is based on Seoul Korean, the phonetic realization of syllable codas in Seoul Korean has not been satisfactorily investigated. This paper aims to study how Seoul speakers pronounce syllable codas in certain phonetic contexts and what pronunciation they prefer among variants. It is noted that the realization of a syllable coda is different word by word and generation by generation. It is also noted that the syllable coda of a word is realized differently depending on the following vowel. And we discussed how the Principles of Standard Korean Pronunciation should be revised in the future, based on the results of this study.

• Speech Sciences
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• v.7 no.2
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• pp.245-253
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• 2000

In this paper, we implement an elementary system to correct accents and pronunciations in English words spoken by non-native English speakers. In case of the accent evaluation, energy and pitch information are used to find stressed syllables, and then we extract the segment information of input patterns using a dynamic time warping method to discriminate and evaluate accent position. For the pronunciation evaluation, we utilize the segment information using the same algorithm as in accent evaluation, and perform the spectral distance measure for each phoneme between input patterns and reference patterns. Based on these spectral distances, we decide whether to recommend the pronunciation correction or not. Our results show that 98 percent of accent and 71 percent of pronunciation evaluation agree with the perceptual measure.

• Speech Sciences
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• v.15 no.3
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• pp.31-38
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• 2008

The aim of this study was to find how English vowels affect the pronunciation of English sibilants /$d_3,\;{_3}$, z/ by Korean learners of English. Fifteen nonsense syllables composed by five vowels /a, e, i, o, u/ were pronounced six times by twelve Korean learners of English. Test scores were measured from the scoreboard made by a speech training software program, which was designed for English pronunciation practice and improvement. Results show that 1) the subjects had the lowest scores in /a_a/ position, and 2) subjects had lower scores in the /i_i/ position than in /e_e/, /o_o/ and /u_u/ positions when they pronounced $/d_3/,\;/{_3}/$, and /z/ in their respective inter-vocalic position. This study found that for the group studied Korean learners of English have more difficulty in pronouncing sibilants in /a_a/ and /i_i/ positions than in the other positions.

• MALSORI
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• no.19_20
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• pp.43-57
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• 1990

The teaching of pronunciation is one of the areas in which linguistic phonetics can play an extremely useful role. This paper is concerned with the application of the results of my phonetic research to the actual teaching of Korean standard pronunciation with special reference to speech rhythm. It has been found that Korean words and utterances of various lengths are pronounced in standard Korean with one of the four main rhythmic patterns, each containing a strong stress. Unless we get the rhythmic patterns right in pronouncing Korean words and utterances, therefore, the resulting pronounciation is bound to sound dialectal or incorrect and in many instances even unintelligible to listeners. Hence the undeniable need to devise a useful technique to teach the Korean speech rhythm in a systematic way. In this paper each of the four main rhythmic patterns is presented and elaborated with sample examples taken from the living Korean. It is hoped that these examples of words and utterances can be used at the same time as useful pronunciation drill material not only for Koreans with dialectal background but also for foreign learners of Korean.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.183-186
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• 2007

This study analyzes Korean high school students' pronunciation errors in word-initial onglides in English. For this study, 24 Korean high school students read 34 English words including glide-vowel sequences in word-initial positions and vowel-initial words in a frame sentence. The results showed 2 different error types: glide deletion and vowel distortion. After the analysis of the first recording, the subjects were taught how to pronounce glide-vowel sequences properly in a 60-minute class. Comparison of the analyses of the first and second recordings showed that the subjects improved on the pronunciation of glide-vowel sequences. After the training, the pronunciation errors of diphthongs unique to English, [$j_I$], decreased substantially. However, most subjects still had difficulties in pronouncing [$w{\mho}$], [wu], and [wo]. There was no significant correlation between English course grade and error reduction.

• Speech Sciences
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• v.11 no.2
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• pp.217-226
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• 2004

An automatic pronunciation correction system provides users with correction guidelines for each pronunciation error. For this purpose, we develop a speech recognition system which automatically classifies pronunciation errors when Koreans speak a foreign language. In this paper, we propose a machine scoring method for automatic assessment of pronunciation quality by the speech recognizer. Scores obtained from an expert human listener are used as the reference to evaluate the different machine scores and to provide targets when training some of algorithms. We use a log-likelihood score and a normalized log-likelihood score as machine scoring methods. Experimental results show that the normalized log-likelihood score had higher correlation with human scores than that obtained using the log-likelihood score.

• MALSORI
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• no.47
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• pp.51-72
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• 2003

The purpose of this paper is to design Speech Database for Korean pronunciation education. For this purpose, I investigated types of speech errors of Korean-learners, made texts for recording, which involves all types of speech errors, and showed how to gather speech data and how to tag their informations. It's natural that speech data should include Korean-learners' speech and Korean people's speech, because Speech DB that I try to develop is for teaching Korean pronunciation to foreigners. So this DB should have informations about speakers and phonetic informations, which are about phonetic value of segments and intonation of sentences. The intonation of sentence varies with the type of sentence, the structure of prosodic units, the length of a prosodic unit and so on. For this reason, Speech DB must involve tags about these informations.

• Proceedings of the KSPS conference
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• 2000.07a
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• pp.241-254
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• 2000

The past decade has witnessed the abundant use of computer in testing language skills such as listening and reading. Compared with these language skills, we have experienced little use of computer in testing a speaking skill including pronunciation. This is largely due to limitations of the current computer technology. One of such limitations for testing pronunciation is to store and automatically evaluate what the learner utters. Due to this limitation, the computer simply stores what the learner utters and raters evaluate it afterward on a certain rating continuum. With the advent of voice recognition technology, however, the computer has been able to test pronunciation in a systematic way. This technology enables the computer to identify, visually show, and evaluate the learner's intonation pattern by means of autocorrection. The evaluation is expressed in terms of the degree in which the learner's intonation pattern overlaps with that of the native speaker of the target language. In particular, the degree is numerically displayed on the screen, and this numeral is considered as the score of the learner's utterance under our testing framework.