• 제목/요약/키워드: 발음 오류

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The effect of eueing technique in acquired Hangul dyslexia (후천성 한글 난독증에서의 단서 주기 효과)

  • 조경덕;이광오
    • Proceedings of the Korean Society for Cognitive Science Conference
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    • 2000.05a
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    • pp.292-296
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    • 2000
  • 뇌손상에 기인하는 한글 난독증의 어휘처리 양상을 분석하여 한글정보처리의 특성을 알아보고자 하였다. 피험자 PSK의 한글 어휘처리에서 특히 주목되는 점은 단어의 음독은 가능하나, 비단어의 음독은 불가능하였다는 것이다. PSK의 한글 어휘처리는, 자소-음소변환(grapheme-phoneme conversion)경로가 선택적으로 손상되어, 심성어휘집(mental lexicon)의 발음정보를 이용하는 직접경로에 의해서 이루어진다고 판단된다. 읽기(reading)와 그림명명(picture naming)에서 나타난 오류들에 대하여, 음운적 단서(phonological cueing)를 제시하였다. 그 결과, 읽기 수행에서는 단서 주기 효과가 나타나지 않았으나 그림명명에서는 수행상의 향상이 나타났다. 또한, 1음절어의 읽기 수행에서는 규칙효과가 나타나지 않았으나 2음절어의 읽기 수행에서는 빈도와 규칙성의 상호작용이 나타났다. 이것은, PSK의 1음절어와 2음절어에 대한 읽기 수행이 상이한 경로에서 이루어질 가능성을 시사한다.

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MCE Training Algorithm for a Speech Recognizer Detecting Mispronunciation of a Foreign Language (외국어 발음오류 검출 음성인식기를 위한 MCE 학습 알고리즘)

  • Bae, Min-Young;Chung, Yong-Joo;Kwon, Chul-Hong
    • Speech Sciences
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    • v.11 no.4
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    • pp.43-52
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    • 2004
  • Model parameters in HMM based speech recognition systems are normally estimated using Maximum Likelihood Estimation(MLE). The MLE method is based mainly on the principle of statistical data fitting in terms of increasing the HMM likelihood. The optimality of this training criterion is conditioned on the availability of infinite amount of training data and the correct choice of model. However, in practice, neither of these conditions is satisfied. In this paper, we propose a training algorithm, MCE(Minimum Classification Error), to improve the performance of a speech recognizer detecting mispronunciation of a foreign language. During the conventional MLE(Maximum Likelihood Estimation) training, the model parameters are adjusted to increase the likelihood of the word strings corresponding to the training utterances without taking account of the probability of other possible word strings. In contrast to MLE, the MCE training scheme takes account of possible competing word hypotheses and tries to reduce the probability of incorrect hypotheses. The discriminant training method using MCE shows better recognition results than the MLE method does.

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Korean-English statistical speech translation Using n-best re-ranking (n-best 리랭킹을 이용한 한-영 통계적 음성 번역)

  • Lee, Dong-Hyeon;Lee, Jong-Hoon;Lee, Gary Geun-Bae
    • Annual Conference on Human and Language Technology
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    • 2006.10e
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    • pp.171-176
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    • 2006
  • 본 논문에서는 n-best 리랭킹을 이용한 한-영 통계적 음성 번역 시스템에 대해 논하고 있다. 보통의 음성 번역 시스템은 음성 인식 시스템, 자동 번역 시스템, 음성 합성 시스템이 순차적으로 결합되어 있다. 하지만 본 시스템은 음성 인식 오류에 보다 강인한 시스템을 만들기 위해 음성 인식 시스템으로부터 n-best 인식 문장을 추출하여 번역 결과와 함께 리랭킹의 과정을 거친다. 자동 번역 시스템으로 구절기반 통계적 자동 번역 모델을 사용하여, 음성 인식기의 발음 모델에서 기본 단어 단위와 맞추어 번역 모델과 언어 모델을 훈련시킴으로써 음성 번역 시스템에서 형태소 분석기를 제거할 수 있다. 또한 음성 인식 시스템에서 상황 별로 언어 모델을 분리하여 처리함으로써 자동 번역 시스템에 비해 부족한 음성 인식 시스템의 처리 범위를 보완할 수 있었다.

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The Prosodic Changes of Korean English Learners in Robot Assisted Learning (로봇보조언어교육을 통한 초등 영어 학습자의 운율 변화)

  • In, Jiyoung;Han, JeongHye
    • Journal of The Korean Association of Information Education
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    • v.20 no.4
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    • pp.323-332
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    • 2016
  • A robot's recognition and diagnosis of pronunciation and its speech are the most important interactions in RALL(Robot Assisted Language Learning). This study is to verify the effectiveness of robot TTS(Text to Sound) technology in assisting Korean English language learners to acquire a native-like accent by correcting the prosodic errors they commonly make. The child English language learners' F0 range and speaking rate in the 4th grade, a prosodic variable, will be measured and analyzed for any changes in accent. We compare whether robot with the currently available TTS technology appeared to be effective for the 4th graders and 1st graders who were not under the formal English learning with native speaker from the acoustic phonetic viewpoint. Two groups by repeating TTS of RALL responded to the speaking rate rather than F0 range.

Analysis of the typology of errors in French's pronunciation by Arabs and proposition for the phonetic correction: Based on the Younes's research paper (아랍어권 학습자들에 의한 프랑스어 발음 오류의 유형 분류와 개선 방안: Younes의 논문을 중심으로)

  • JUNG, Il-Young
    • Cross-Cultural Studies
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    • v.27
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    • pp.7-29
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    • 2012
  • This study was aimed to analyze - focusing on the thesis of Younes - the pronunciation error occuring mostly for Arabian speakers to learn French pronunciation for Arabians and to suggest the effective study plan to improve such errors and provide the effective studying method. The first part is on how the Arabic and French pronunciation system are distinguished, especially by comparing and analyzing the system of graphemes and phonemes, with which we focused on the fact that Arabian is a language centralized on consonants, while French is a verb-centered language. In the second part, we mainly discussed the cause and the types of errors occurring when Arabic speakers study French pronunciation. As of the category of mistakes, we separated them into consonants and verbs. We assumed the possible method which can be used in learning, focusing on /b/, /v/, /p/, /b/ - in case of non-verbs and consonants - and /y/, /ø/, - in case of verbs - which don't exist in Arabic pronunciation system. One of the troubles the professors in Arabian culture have in teaching French to native learners is how to solve the problem on a phonetic basis regarding speaking and reading ability, which belong to verbal skill, among the critical factors of foreign language education, which are listening, speaking, reading, and writing skills. In fact, the problems occuring in learning foreign language are had by not only Arabian learners but also general groups of people who learn the foreign language, the pronunciation system of which is distinctly distinguished from their mother tongue. The important fact professors should recognize regarding study of pronunciation is that they should encourage the learners to reach the acceptable level in proper communication rather than push them to have the same ability as the native speakers, Even though it cannot be said that the methods suggested in this study have absolute influence in reducing errors when learning French pronunciation system, I hope it can be at least a small help.

Effects of Forest Healing Programs Using School Forests on Language Acquisition and Ego-resilience of Multicultural Background Students (학교 숲을 활용한 산림치유프로그램 활동이 다문화배경 학생들의 언어습득 향상과 자아탄력성에 미치는 영향)

  • Jang, Cheoul-Soon;Shin, Chang-Seob;Jang, Byung-Soon;Sharif, Md. Omar
    • Korean Journal of Environment and Ecology
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    • v.33 no.3
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    • pp.333-340
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    • 2019
  • As the number of students in the multicultural background grows, the interest in their education is also increasing. The purpose of this study is to investigate the effect of forest healing factors on the improvement of language ability and ego-resilience of students from multicultural families. We conducted an after-school forest healing program of ten male and ten female middle school students of a multicultural preparatory school located in ${\bigcirc}{\bigcirc}$-dong in Cheongju, Chungnam Province. The experiment consisted of a total of 12 weekly one-hour (60 minutes) programs from April 12, 2018 to June 26, 2018. The forest healing program is an activity that uses the various environmental factors that exist in the forest to increase the immunity of the human body and restore physical and mental health. To determine the difference in ego-resilience before and after the program, we conducted a paired t-test and analyzed with the SPSS 18.0 program. The results showed that the ego-resilience significantly improved in all sub-factors including the positive thinking ability, problem-solving ability, intimacy ability, emotional adjustment ability, and autonomic behavior ability (p<.001). The descriptive statistics of the language ability showed the improvement in writing errors, pronunciation errors, sentence errors, tense errors, and errors in research and connection. We expect the results of this study can be used as the basic data to improve ego-resilience and language acquisition ability of middle-entry children and students from multicultural families.

A Study on the Utilization of Speech Recognition Technology in Foreign Language Learning Applications - Focusing on English and French Speech - (외국어 학습용 어플리케이션의 음성 인식 기술 활용 현황 - 영어와 프랑스어 말하기 학습을 중심으로 -)

  • Kim, Sunhee;Jung, Hyunhoon
    • Journal of Digital Contents Society
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    • v.19 no.4
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    • pp.621-630
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    • 2018
  • This paper presents a case study on foreign language learning applications based on the speech recognition technology, aiming to grasp their current status and limitations of the technology applied to the foreign language speaking education, especially for English and French. As a result of examining the characteristics of the selected English and French applications by drawing on speech learning, it is shown that the use of speech recognition technology has the advantage of creating a speaking practice environment and giving feedback. However, in the case of feedback, there is a lack of appropriate calibration feedback which can help learners correct errors by themselves.

Korean Spacing System for Continuous Speech Characters (연속 음성 문자열에 대한 한국어 띄어쓰기 시스템)

  • Kim, Kye-Sung;Lee, Hyun-Ju;Kim, Sung-Kyu;Choi, Jae-Hyuk;Lee, Sang-Jo
    • Annual Conference on Human and Language Technology
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    • 1998.10c
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    • pp.391-395
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    • 1998
  • 대용량의 연속된 음성을 인식하는 데에는 형태소 사이의 음운변동과 언절과 어절 사이의 불일치 등으로 인한 어려움이 따른다. 그러므로 언어학적인 지식을 이용한 자연어 처리 기술과의 결합이 필수적이라 할 수 있다. 본 논문에서는 문장 단위의 연속 음성 문자열을 올바른 어절로 띄어주는 시스템을 제안한다. 먼저 띄어쓰기 발음열 사전을 이용하여 어절의 경계를 추정한다. 이 때 보다 정확한 띄어쓰기 위치를 추정하기 위하여 2음절 이상의 최장 조사 어미와 음절 분리가능빈도가 이용된다. 이렇게 해서 분리된 어절들은 음절 복원기를 거친 뒤, 형태소 분석을 행하여 올바른 어절인지를 검사한다. 분석에 실패한 어절은 띄어쓰기 오류 유형에 따라 교정을 한 후 형태소 분석을 재시도한다. 제안한 시스템을 테스트해 본 결과 96.8%의 정확도를 보였다. 본 시스템은 음운 변동 처리기와 함께 말소리를 음성 그대로 인식하는 인식기의 후처리로 이용할 수 있을 것이다.

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Acoustic Analysis of Koreans' Production Errors in English - with reference to nasalization and lateralization (한국인 화자의 영어 발음 오류에 관한 음향적 분석 - 비음화와 설측음화를 중심으로 -)

  • Kim, Mi-Hye;Kang, Sun-Mi;Kim, Kee-Ho
    • Speech Sciences
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    • v.15 no.3
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    • pp.53-63
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    • 2008
  • This paper examined the acoustic differences in English speech production between English native speakers and Korean learners. Korean speakers seem to produce errors by over-applying the Korean phonological rules(nasalization and lateralization) to English speech under the conditions comparable to those of Korean which contain nasal+lateral or lateral+nasal sequences. Being based on this prediction, the experimental data is grouped into three sets, [n]+[l] sequence, [l]+[n]sequence, and [m]+[l] sequence. The result shows that, Korean speakers usually nasalize or lateralize the target words or phrases in every three categories while English natives don't. In set A([n]+[l] sequence), both nasalization and lateralization were found in [n]+[l] sequence, the same circumstances where both nasalization and lateralization can be placed as in Korean. In the case of set B([l]+[n] sequence), only lateralization is observed. It is because the nasalization never occurs in the sequence of l-n in Korean. There is no lateralization in set C([m]+[l] sequence), because only nasalization occurs in the sequence of m-l in Korean. This results reconfirmed that the nasalization and lateralization rules in Korean deeply influence on the English production data. Korean speakers need to be taught not to over-apply Korean phonological rule to English production for accurate pronunciation.

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Generation and Recognition Language Model for Spoken Language Parser (구어파서를 위한 생성 인식 언어모델)

  • Jeong, Hong;Hwang, Kwang-Il
    • Annual Conference on Human and Language Technology
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    • 1999.10e
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    • pp.167-172
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    • 1999
  • 구어는 프로그래밍 언어와는 달리 주어진 문장 내에서의 해당 어휘의 뜻(semantic information)을 알고 다른 어휘들과의 연관성 (grammatical information)을 알아야만 적절한 형태소분석이 가능하다. 또한 구어는 방대한 양의 어휘들로 구성되어 있으며 사용하는 사람마다의 다양한 응용과 공식화되기 어려운 수많은 예외들로 운용되기 때문에 단순히 찾아보기표와 오토마타만으로는 형태소분석에 한계가 있다. 이에 본 논문에서는 주어진 어휘집과 그 어휘들로 만들어진 다양한 문장들로부터 구어운용의 근본기제를 스스로 학습해나가는 강화학습중심의 언어모델을 제안하고 실제로 한국어 형태소분석에 적용하여 그 성능과 특성을 파악해보았다. 구어파서의 입력은 음절단위의 발음이며 인간이 문장을 듣거나 보는 것과 동일하게 시간에 따라 순차적으로 입력된다. 파서의 출력 또한 시간에 따라 변화되면서 나타나며 입력된 연속음절을 형태소단위로 분리(segmentation)하고 분류(labeling)한 결과를 나타낸다. 생성인식 언어모델이 기존의 언어모델과 다른 점은 구어 파싱에 있어서 필수적인 미등륵어에 대한 유연성과 앞단의 음성인식기 오류에 적절한 반응(fault tolerance)을 나타내는 것이다.

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