• Title/Summary/Keyword: Korean pronunciation

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A Study on the Korean Language Acquisition of Children from Chinese Families in Korea: Focusing on Pronunciation and Vocabulary (재한중국인 가정 아동의 한국어 습득에 관한 연구 -발음과 어휘를 중심으로-)

  • Li, Yin
    • Journal of Korean language education
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    • v.29 no.3
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    • pp.165-196
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    • 2018
  • This study examined the language acquisition of children from Chinese families in Korea under the bilingual background of Korean and Chinese, focusing on pronunciation and vocabulary. First, in the analysis of pronunciation acquisition, children correctly realized the lenition, aspirated sound, glottalization, palatalization, nasalization, and liquidization while the realization of pronunciation rules for unfamiliar words was low. There were also errors caused when the application principles of pronunciation were not accurately understood or they were not partially acquired. Second, in the analysis of vocabulary acquisition, the acquisition of receptive vocabulary was in the order of verb, noun, and adjective while they clearly understood vocabulary used in the actual relationships with school, family, and peers. In the acquisition of productive vocabulary, they showed the 'meaning-centered principle' of learning the meaning of vocabulary first and then learning its form afterwards. The amount of study and exposure to Korean language had effects on the improvement of vocabulary. Even though this study focused on the errors and characteristics in the acquisition process of Korean pronunciation and vocabulary for children from Chinese families in Korea, it could not clearly find out which one would have greater effects on the acquisition of Korean language. However, lots of exchanges and experiences with surrounding environment and peer group had great effects on the language acquisition and language acquisition transfer of children.

Automatic pronunciation assessment of English produced by Korean learners using articulatory features (조음자질을 이용한 한국인 학습자의 영어 발화 자동 발음 평가)

  • Ryu, Hyuksu;Chung, Minhwa
    • Phonetics and Speech Sciences
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    • v.8 no.4
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    • pp.103-113
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    • 2016
  • This paper aims to propose articulatory features as novel predictors for automatic pronunciation assessment of English produced by Korean learners. Based on the distinctive feature theory, where phonemes are represented as a set of articulatory/phonetic properties, we propose articulatory Goodness-Of-Pronunciation(aGOP) features in terms of the corresponding articulatory attributes, such as nasal, sonorant, anterior, etc. An English speech corpus spoken by Korean learners is used in the assessment modeling. In our system, learners' speech is forced aligned and recognized by using the acoustic and pronunciation models derived from the WSJ corpus (native North American speech) and the CMU pronouncing dictionary, respectively. In order to compute aGOP features, articulatory models are trained for the corresponding articulatory attributes. In addition to the proposed features, various features which are divided into four categories such as RATE, SEGMENT, SILENCE, and GOP are applied as a baseline. In order to enhance the assessment modeling performance and investigate the weights of the salient features, relevant features are extracted by using Best Subset Selection(BSS). The results show that the proposed model using aGOP features outperform the baseline. In addition, analysis of relevant features extracted by BSS reveals that the selected aGOP features represent the salient variations of Korean learners of English. The results are expected to be effective for automatic pronunciation error detection, as well.

Pronunciation Lexicon Optimization with Applying Variant Selection Criteria (발음 변이의 발음사전 포함 결정 조건을 통한 발음사전 최적화)

  • Jeon, Je-Hun;Chung, Min-Hwa
    • Proceedings of the KSPS conference
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    • 2006.11a
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    • pp.24-27
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    • 2006
  • This paper describes how a domain dependent pronunciation lexicon is generated and optimized for Korean large vocabulary continuous speech recognition(LVCSR). At the level of lexicon, pronunciation variations are usually modeled by adding pronunciation variants to the lexicon. We propose the criteria for selecting appropriate pronunciation variants in lexicon: (i) likelihood and (ii) frequency factors to select variants. Our experiment is conducted in three steps. First, the variants are generated with knowledge-based rules. Second, we generate a domain dependent lexicon which includes various numbers of pronunciation variants based on the proposed criteria. Finally, the WERs and RTFs are examined with each lexicon. In the experiment, 0.72% WER reduction is obtained by introducing the variants pruning criteria. Furthermore, RTF is not deteriorated although the average number of variants is higher than that of compared lexica.

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Digital enhancement of pronunciation assessment: Automated speech recognition and human raters

  • Miran Kim
    • Phonetics and Speech Sciences
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    • v.15 no.2
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    • pp.13-20
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    • 2023
  • This study explores the potential of automated speech recognition (ASR) in assessing English learners' pronunciation. We employed ASR technology, acknowledged for its impartiality and consistent results, to analyze speech audio files, including synthesized speech, both native-like English and Korean-accented English, and speech recordings from a native English speaker. Through this analysis, we establish baseline values for the word error rate (WER). These were then compared with those obtained for human raters in perception experiments that assessed the speech productions of 30 first-year college students before and after taking a pronunciation course. Our sub-group analyses revealed positive training effects for Whisper, an ASR tool, and human raters, and identified distinct human rater strategies in different assessment aspects, such as proficiency, intelligibility, accuracy, and comprehensibility, that were not observed in ASR. Despite such challenges as recognizing accented speech traits, our findings suggest that digital tools such as ASR can streamline the pronunciation assessment process. With ongoing advancements in ASR technology, its potential as not only an assessment aid but also a self-directed learning tool for pronunciation feedback merits further exploration.

A Study on Construction and Implementation of Web education System with Chinese conversion rule set (중국어 규칙변환 웹 교육시스템 설계 및 구현에 관한 연구)

  • Lee, Ji Hyun;Lee, Eun Ryoung
    • Journal of Digital Contents Society
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    • v.17 no.4
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    • pp.227-234
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    • 2016
  • When Chinese character used in Korea, so did the characters' pronunciation, so many Korean Chinese characters today have similar pronunciation with Chinese, but since Korean and Chinese pronunciations were preserved and developed in different alphabets, the written letter of the pronunciation also differs. This study on Chinese education, has constructed and implemented an easy way to study Chinese pronunciations by creating conversion rule set between Chinese pronunciation, Chinese Hanyu latin Pinyin and Korean chinese character pronunciation consisting of an initial sound, a medial vowel, and a final consonant. This study has established web version and application version of this conversion rule set education system to enhance Chinese education.

Performance of speech recognition unit considering morphological pronunciation variation (형태소 발음변이를 고려한 음성인식 단위의 성능)

  • Bang, Jeong-Uk;Kim, Sang-Hun;Kwon, Oh-Wook
    • Phonetics and Speech Sciences
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    • v.10 no.4
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    • pp.111-119
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    • 2018
  • This paper proposes a method to improve speech recognition performance by extracting various pronunciations of the pseudo-morpheme unit from an eojeol unit corpus and generating a new recognition unit considering pronunciation variations. In the proposed method, we first align the pronunciation of the eojeol units and the pseudo-morpheme units, and then expand the pronunciation dictionary by extracting the new pronunciations of the pseudo-morpheme units at the pronunciation of the eojeol units. Then, we propose a new recognition unit that relies on pronunciation by tagging the obtained phoneme symbols according to the pseudo-morpheme units. The proposed units and their extended pronunciations are incorporated into the lexicon and language model of the speech recognizer. Experiments for performance evaluation are performed using the Korean speech recognizer with a trigram language model obtained by a 100 million pseudo-morpheme corpus and an acoustic model trained by a multi-genre broadcast speech data of 445 hours. The proposed method is shown to reduce the word error rate relatively by 13.8% in the news-genre evaluation data and by 4.5% in the total evaluation data.

An evaluation of Korean students' pronunciation of an English passage by a speech recognition application and two human raters

  • Yang, Byunggon
    • Phonetics and Speech Sciences
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    • v.12 no.4
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    • pp.19-25
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    • 2020
  • This study examined thirty-one Korean students' pronunciation of an English passage using a speech recognition application, Speechnotes, and two Canadian raters' evaluations of their speech according to the International English Language Testing System (IELTS) band criteria to assess the possibility of using the application as a teaching aid for pronunciation education. The results showed that the grand average percentage of correctly recognized words was 77.7%. From the moderate recognition rate, the pronunciation level of the participants was construed as intermediate and higher. The recognition rate varied depending on the composition of the content words and the function words in each given sentence. Frequency counts of unrecognized words by group level and word type revealed the typical pronunciation problems of the participants, including fricatives and nasals. The IELTS bands chosen by the two native raters for the rainbow passage had a moderately high correlation with each other. A moderate correlation was reported between the number of correctly recognized content words and the raters' bands, while an almost a negligible correlation was found between the function words and the raters' bands. From these results, the author concludes that the speech recognition application could constitute a partial aid for diagnosing each individual's or the group's pronunciation problems, but further studies are still needed to match human raters.

The Study on Automatic Speech Recognizer Utilizing Mobile Platform on Korean EFL Learners' Pronunciation Development (자동음성인식 기술을 이용한 모바일 기반 발음 교수법과 영어 학습자의 발음 향상에 관한 연구)

  • Park, A Young
    • Journal of Digital Contents Society
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    • v.18 no.6
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    • pp.1101-1107
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    • 2017
  • This study explored the effect of ASR-based pronunciation instruction, using a mobile platform, on EFL learners' pronunciation development. Particularly, this quasi-experimental study focused on whether using mobile ASR, which provides voice-to-text feedback, can enhance the perception and production of target English consonants minimal pairs (V-B, R-L, and G-Z) of Korean EFL learners. Three intact classes of 117 Korean university students were assigned to three groups: a) ASR Group: ASR-based pronunciation instruction providing textual feedback by the mobile ASR; b) Conventional Group: conventional face-to-face pronunciation instruction providing individual oral feedback by the instructor; and the c) Hybrid Group: ASR-based pronunciation instruction plus conventional pronunciation instruction. The ANCOVA results showed that the adjusted mean score for pronunciation production post-test on the Hybrid instruction group (M=82.71, SD =3.3) was significantly higher than the Conventional group (M=62.6, SD =4.05) (p<.05).

Redefining Lingua Franca Core for Korean Learners of English

  • Chung, Hyun-Song
    • Phonetics and Speech Sciences
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    • v.2 no.4
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    • pp.129-134
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    • 2010
  • Jenkins (2000, 2007) suggested lingua franca core (LFC) of English as an international language (EIL) context. According to her, intelligibility of English pronunciation of L2 English speakers and English learners is more important than pronunciation accuracy in English communication. Her suggestion has been widely accepted in Korean classroom situations, so the systematic teaching of English pronunciation has been rarely emphasized. In this paper it is argued that the LFC of English is widely misinterpreted in Korea while some of her suggestions themselves are also misleading. This paper tries to redefine Jenkins' LFC and provide suggestions for teaching LFC in Korea.

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A knowledge-based pronunciation generation system for French (지식 기반 프랑스어 발음열 생성 시스템)

  • Kim, Sunhee
    • Phonetics and Speech Sciences
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    • v.10 no.1
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    • pp.49-55
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    • 2018
  • This paper aims to describe a knowledge-based pronunciation generation system for French. It has been reported that a rule-based pronunciation generation system outperforms most of the data-driven ones for French; however, only a few related studies are available due to existing language barriers. We provide basic information about the French language from the point of view of the relationship between orthography and pronunciation, and then describe our knowledge-based pronunciation generation system, which consists of morphological analysis, Part-of-Speech (POS) tagging, grapheme-to-phoneme generation, and phone-to-phone generation. The evaluation results show that the word error rate of POS tagging, based on a sample of 1,000 sentences, is 10.70% and that of phoneme generation, using 130,883 entries, is 2.70%. This study is expected to contribute to the development and evaluation of speech synthesis or speech recognition systems for French.