• 대한음성학회지:말소리
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• 제49호
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• pp.123-134
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• 2004

An automatic pronunciation correction system provides learners with correction guidelines for each mispronunciation. In this paper we propose an HMM based speech recognizer which automatically classifies pronunciation errors when Koreans speak Japanese. We also propose two pronunciation networks for automatic detection of mispronunciation. In this paper, we evaluated performances of the networks by computing the correlation between the human ratings and the machine scores obtained from the speech recognizer.

• 대한음성학회지:말소리
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• 제46호
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• pp.87-102
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• 2003

In this paper, we present an English pronunciation correction system for Korean speakers and show some of experimental results on it. The aim of the system is to detect mispronounced phonemes in spoken words and to give appropriate correction comments to users. There are several English pronunciation correction systems adopting speech recognition technology, however, most of them use conventional speech recognition engines. From this reason, they could not give phoneme based correction comments to users. In our system, we build two kinds of phoneme models: standard native speaker models and Korean's error models. We also design recognition network based on phonemes to detect Koreans' common mispronunciations. We get 90% detection rate in insertion/deletion/replacement of phonemes, but we cannot get high detection rate in diphthong split and accents.

• 컴퓨터교육학회논문지
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• 제18권4호
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• pp.11-18
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• 2015

청력의 결여나 결손이 생기면 회화 음이나 환경 음을 청취하는 것이 어려우므로 언어 감각, 성격 등에 문제가 발생한다. 이러한 청각장애인들을 위하여 특별하게 발음 교정 교육을 할 수 있는 응용 프로그램을 설계하고 구현하였다. 시간과 장소에 제약이 없이 사용할 수 있도록 스마트폰 앱 형태로 제작하였고, 청각장애인의 발음 교정 실태를 고려하여 발음 습득 순서에 따라 난이도 순 훈련을 제공한다. 기본 발음 연습, 단어 발음 연습을 할 수 있고, 이에 대한 기록을 통하여 연습률과 성공률을 확인할 수 있다. 또한, 전면카메라를 통한 자가 발음 교정이 가능하도록 하여 발음이 향상되도록 하였다.

• 대한음성학회지:말소리
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• 제49호
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• pp.95-105
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• 2004

An automatic pronunciation correction system provides learners with correction guidelines for each mispronunciation. For this purpose we develope a speech recognizer which automatically classifies pronunciation errors when Koreans speak a foreign language. In order to develope the methods for automatic assessment of pronunciation quality, we propose a language model based score as a machine score in the speech recognizer. Experimental results show that the language model based score had higher correlation with human scores than that obtained using the conventional log-likelihood based score.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 10월 학술대회지
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• pp.29-32
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• 2003

This paper proposes an automatic pronunciation correction system which provides users with correction guidelines for each pronunciation error. For this purpose, we develop an HMM speech recognizer which automatically classifies pronunciation errors when Korean speaks foreign language. And, we collect speech database of native and nonnative speakers using phonetically balanced word lists. We perform analysis of mispronunciation types from the experiment of automatic mispronunciation detection using speech recognizer.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2004년도 춘계 학술대회 발표논문집
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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.

• 음성과학
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• 제7권2호
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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.

• 음성과학
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• 제11권2호
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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.

• 대한음성학회지:말소리
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• 제48호
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• pp.127-139
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• 2003

An automatic pronunciation correction system provides learners with correction guidelines for each mispronunciation. In this paper we propose an HMM based speech recognizer which automatically classifies pronunciation errors when Korean speak Japanese. For this purpose we also develop phoneme recognizers for Korean and Japanese. Experimental results show that the machine scores of the proposed recognizer correlate with expert ratings well.

• 말소리와 음성과학
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• 제5권2호
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• pp.81-90
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• 2013

The purposes of this study are to: (1) Compare the vowel production of English front vowels produced by Korean speakers using regional dialects and; (2) Investigate and compare the effectiveness of pronunciation training for each regional dialect group. To test these objectives, the English front vowels produced by five Youngnam dialect male speakers, five Youngnam dialect female speakers, five Kangwon dialect male speakers, and five Kangwon dialect female speakers were scrutinized. These dialect groups' vowel formants and length of English front vowels were evaluated, and the post-pronunciation training values were compared with those of pre-training values. The results indicate that pronunciation training is more effective for Youngnam dialect speakers, whilst both dialect groups have more success mastering the pronunciation of /${\varepsilon}$/ over /${\ae}$/.